6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis...

120
6.6: Maximum flow Frank Stajano Thomas Sauerwald Lent 2016 s 2 3 4 5 t Graph G =(V, E, c): 8/10 8/9 8/8 2/4 8/10 10/10 9/10 0/2 6/6 3/4 7/8 9/9 9/10 10/10 s 2 3 4 5 t Residual Graph Gf =(V, Ef , cf ): 10 2 8 2 6 2 2 8 1 8 2 8 10 |f | = 18

Transcript of 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis...

Page 1: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

6.6: Maximum flowFrank Stajano Thomas Sauerwald

Lent 2016

Illustration of the Ford-Fulkerson Method

s

2

3

4

5 t

Graph G = (V , E , c):

0/10

0/10

0/2 0/6

0/4

0/8

0/9

0/10

0/10

⇠⇠

0/10 ��0/8

⇠⇠0/108/1

0

0/10

0/2 0/6

0/4

8/8

0/9

0/10

8/10

⇠⇠

8/10 ��0/2

��0/9⇠⇠8/10

10/10

0/10

2/2 0/6

0/4

8/8

2/9

0/10

10/10⇠⇠0/10

��2/9

��0/6⇠⇠0/1010

/10

6/10

2/2 6/6

0/4

8/8

8/9

6/10

10/10⇠⇠6/10

��2/2

��0/4

⇠⇠6/1010/10

8/10

0/2 6/6

2/4

8/8

8/9

8/10

10/10

⇠⇠8/10 ��8/9

��8/8

��2/4⇠⇠8/1010

/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

s

2

3

4

5 t

Residual Graph Gf = (V , Ef , cf ):

10

10

2 6

4

8

9

10

10

2

8

10

2 6

4

8

9

10

2

8

10

10

2 6

4

8

7

2

10

10

10

4

6

2 6

4

8

1

8

4

6

10

10

2

8

2 6

2

2

8

1

8

2

8

10

10

1

9

2 6

1

3

7

1

9

1

9

10

|f | = 0|f | = 8|f | = 10|f | = 16

|f | = 18

|f | = 19

Is this a max-flow?

6.6: Maximum flow T.S. 9

Page 2: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Outline

A Glimpse at the Max-Flow Min-Cut Theorem

Analysis of Ford-Fulkerson

Matchings in Bipartite Graphs

6.6: Maximum flow T.S. 11

Page 3: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

A cut (S,T ) is a partition of V into S and T = V \ S such that s ∈ Sand t ∈ T .

The capacity of a cut (S,T ) is the sum of capacities of the edgesfrom S to T :

c(S,T ) =∑

u∈S,v∈T

c(u, v) =∑

(u,v)∈E(S,T )

c(u, v)

A minimum cut of a network is a cut whose capacity is minimumover all cuts of the network.

Cut

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) =

10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 4: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

A cut (S,T ) is a partition of V into S and T = V \ S such that s ∈ Sand t ∈ T .

The capacity of a cut (S,T ) is the sum of capacities of the edgesfrom S to T :

c(S,T ) =∑

u∈S,v∈T

c(u, v) =∑

(u,v)∈E(S,T )

c(u, v)

A minimum cut of a network is a cut whose capacity is minimumover all cuts of the network.

Cut

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) =

10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 5: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

A cut (S,T ) is a partition of V into S and T = V \ S such that s ∈ Sand t ∈ T .

The capacity of a cut (S,T ) is the sum of capacities of the edgesfrom S to T :

c(S,T ) =∑

u∈S,v∈T

c(u, v) =∑

(u,v)∈E(S,T )

c(u, v)

A minimum cut of a network is a cut whose capacity is minimumover all cuts of the network.

Cut

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) =

10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 6: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

A cut (S,T ) is a partition of V into S and T = V \ S such that s ∈ Sand t ∈ T .

The capacity of a cut (S,T ) is the sum of capacities of the edgesfrom S to T :

c(S,T ) =∑

u∈S,v∈T

c(u, v) =∑

(u,v)∈E(S,T )

c(u, v)

A minimum cut of a network is a cut whose capacity is minimumover all cuts of the network.

Cut

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 7: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

A cut (S,T ) is a partition of V into S and T = V \ S such that s ∈ Sand t ∈ T .

The capacity of a cut (S,T ) is the sum of capacities of the edgesfrom S to T :

c(S,T ) =∑

u∈S,v∈T

c(u, v) =∑

(u,v)∈E(S,T )

c(u, v)

A minimum cut of a network is a cut whose capacity is minimumover all cuts of the network.

Cut

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 8: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 9: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 10: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 11: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 19

9 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 12: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 13: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 199 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 14: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flows to Cuts

The value of the max-flow is equal to the capacity of the min-cut, that is

maxf|f | = min

S,T⊆Vc(S,T ).

Theorem (Max-Flow Min-Cut Theorem)

s

2

3

4

5 t

Graph G = (V ,E , c):

10

10

2 6

4

8

9

10

10

c({s, 3}, {2, 4, 5, t}) = 10 + 9 = 19

|f | = 19

10/10

9/10

0/2 6/6

3/4

7/8

9/9

9/10

10/10

10− 0 + 9 = 19

9 + 7− 6 + 9 = 19

6.6: Maximum flow T.S. 12

Page 15: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Extra: Proof of the Max-Flow Min-Cut Theorem (Easy Direction)

1. For every u, v ∈ V , f (u, v) ≤ c(u, v),2. For every u, v ∈ V , f (u, v) = −f (v , u),3. For every u ∈ V \ {s, t},

∑v∈V f (u, v) = 0.

Let f be any flow and (S,T ) be any cut:

|f | =∑v∈V

f (s, v)

(3)=

∑u∈S

∑v∈V

f (u, v)

=∑u∈S

∑v∈S

f (u, v) +∑u∈S

∑v∈T

f (u, v)

(2)=

∑u∈S

∑v∈T

f (u, v)

(1)≤

∑u∈S

∑v∈T

c(u, v)

= c(S,T ).

Since this holds for any pair of flow and cut, it follows thatmax

f|f | ≤ min

(S,T )c(S,T )

Flow-Value-Lemma:For any cut (S,T ),

|f | =∑u∈S

∑v∈T

f (u, v).

6.6: Maximum flow T.S. 12

Page 16: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Outline

A Glimpse at the Max-Flow Min-Cut Theorem

Analysis of Ford-Fulkerson

Matchings in Bipartite Graphs

6.6: Maximum flow T.S. 13

Page 17: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Analysis of Ford-Fulkerson

0: def FordFulkerson(G)1: initialize flow to 0 on all edges2: while an augmenting path in Gf can be found:3: push as much extra flow as possible through it

If all capacities c(u, v) are integral, then the flow at every iteration ofFord-Fulkerson is integral.

Lemma

Flow before iteration integral& capacities in Gf are integral⇒ Flow after iteration integral

For integral capacities c(u, v), Ford-Fulkerson terminates after C :=maxu,v c(u, v) iterations and returns the maximum flow.

Theorem

(proof omitted here, see CLRS3)

6.6: Maximum flow T.S. 14

Page 18: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Analysis of Ford-Fulkerson

0: def FordFulkerson(G)1: initialize flow to 0 on all edges2: while an augmenting path in Gf can be found:3: push as much extra flow as possible through it

If all capacities c(u, v) are integral, then the flow at every iteration ofFord-Fulkerson is integral.

Lemma

Flow before iteration integral& capacities in Gf are integral⇒ Flow after iteration integral

For integral capacities c(u, v), Ford-Fulkerson terminates after C :=maxu,v c(u, v) iterations and returns the maximum flow.

Theorem

(proof omitted here, see CLRS3)

6.6: Maximum flow T.S. 14

Page 19: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Analysis of Ford-Fulkerson

0: def FordFulkerson(G)1: initialize flow to 0 on all edges2: while an augmenting path in Gf can be found:3: push as much extra flow as possible through it

If all capacities c(u, v) are integral, then the flow at every iteration ofFord-Fulkerson is integral.

Lemma

Flow before iteration integral& capacities in Gf are integral⇒ Flow after iteration integral

For integral capacities c(u, v), Ford-Fulkerson terminates after C :=maxu,v c(u, v) iterations and returns the maximum flow.

Theorem

(proof omitted here, see CLRS3)

6.6: Maximum flow T.S. 14

Page 20: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Analysis of Ford-Fulkerson

0: def FordFulkerson(G)1: initialize flow to 0 on all edges2: while an augmenting path in Gf can be found:3: push as much extra flow as possible through it

If all capacities c(u, v) are integral, then the flow at every iteration ofFord-Fulkerson is integral.

Lemma

Flow before iteration integral& capacities in Gf are integral⇒ Flow after iteration integral

For integral capacities c(u, v), Ford-Fulkerson terminates after C :=maxu,v c(u, v) iterations and returns the maximum flow.

Theorem

(proof omitted here, see CLRS3)

6.6: Maximum flow T.S. 14

Page 21: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Analysis of Ford-Fulkerson

0: def FordFulkerson(G)1: initialize flow to 0 on all edges2: while an augmenting path in Gf can be found:3: push as much extra flow as possible through it

If all capacities c(u, v) are integral, then the flow at every iteration ofFord-Fulkerson is integral.

Lemma

Flow before iteration integral& capacities in Gf are integral⇒ Flow after iteration integral

For integral capacities c(u, v), Ford-Fulkerson terminates after C :=maxu,v c(u, v) iterations and returns the maximum flow.

Theorem

(proof omitted here, see CLRS3)

6.6: Maximum flow T.S. 14

Page 22: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

1/1000

1/1000

1/1000

0/1

2/1000

1/1000

1/1000

2/1000

1/1

2/1000

2/1000

2/1000

2/1000

0/1

3/1000

2/1000

2/1000

3/1000

1/1

3/1000

3/1000

3/1000

3/1000

0/1 s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 23: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

1/1000

1/1000

1/1000

0/1

2/1000

1/1000

1/1000

2/1000

1/1

2/1000

2/1000

2/1000

2/1000

0/1

3/1000

2/1000

2/1000

3/1000

1/1

3/1000

3/1000

3/1000

3/1000

0/1 s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 24: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

1/1000

1/1000

1/1000

0/1

2/1000

1/1000

1/1000

2/1000

1/1

2/1000

2/1000

2/1000

2/1000

0/1

3/1000

2/1000

2/1000

3/1000

1/1

3/1000

3/1000

3/1000

3/1000

0/1

s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 25: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

1/1000

1/1000

1/1000

0/1

2/1000

1/1000

1/1000

2/1000

1/1

2/1000

2/1000

2/1000

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0/1

3/1000

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3/1000

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0/1

s

u

v

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Gf

1000

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1

9991

1000

1000

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1

9991

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9991

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1

9982

9991

9991

9982

1

9982

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9982

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1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 26: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

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0/1

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0/1

s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 27: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

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0/1

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Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 28: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

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1000

1000

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1

9991

1000

1000

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1

9991

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9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 29: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

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0/1

s

u

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

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1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 30: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

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3/1000

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0/1

s

u

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 31: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

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0/1

s

u

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 32: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

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0/1

s

u

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 33: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

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0/1

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Gf

1000

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1

9991

1000

1000

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1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 34: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

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0/1

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

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1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 35: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

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3/1000

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0/1

s

u

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 36: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

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2/1000

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3/1000

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0/1

s

u

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t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 37: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

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0/1

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1/1

3/1000

3/1000

3/1000

3/1000

0/1

s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 38: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

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0/1

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2/1000

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1/1

3/1000

3/1000

3/1000

3/1000

0/1

s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 39: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

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0/1

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1/1

3/1000

3/1000

3/1000

3/1000

0/1

s

u

v

t

Gf

1000

1000

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1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 40: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

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0/1

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2/1000

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1/1

3/1000

3/1000

3/1000

3/1000

0/1

s

u

v

t

Gf

1000

1000

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1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 41: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

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1/1

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0/1

3/1000

2/1000

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3/1000

1/1

3/1000

3/1000

3/1000

3/1000

0/1 s

u

v

t

Gf

1000

1000

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1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 42: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

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1/1

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1/1

3/1000

3/1000

3/1000

3/1000

0/1 s

u

v

t

Gf

1000

1000

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1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 43: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

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1/1000

1/1000

0/1

2/1000

1/1000

1/1000

2/1000

1/1

2/1000

2/1000

2/1000

2/1000

0/1

3/1000

2/1000

2/1000

3/1000

1/1

3/1000

3/1000

3/1000

3/1000

0/1 s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 44: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Slow Convergence of Ford-Fulkerson (Figure 26.7)

s

u

v

t

G

0/1000

0/1000

0/1000

0/1000

0/1

1/1000

0/1000

0/1000

1/1000

1/1

1/1000

1/1000

1/1000

1/1000

0/1

2/1000

1/1000

1/1000

2/1000

1/1

2/1000

2/1000

2/1000

2/1000

0/1

3/1000

2/1000

2/1000

3/1000

1/1

3/1000

3/1000

3/1000

3/1000

0/1 s

u

v

t

Gf

1000

1000

1000

1000

1

9991

1000

1000

9991

1

9991

9991

9991

9991

1

9982

9991

9991

9982

1

9982

9982

9982

9982

1

9973

9982

9982

9973

1

9973

9973

9973

9973

1

Number of iterations is C := maxu,v c(u, v)!

For irrational capacities, Ford-Fulkersonmay even fail to terminate!

6.6: Maximum flow T.S. 15

Page 45: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 46: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 47: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1 0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 48: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1 0/1 0/φ

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 49: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1 0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 50: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1 0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

1 1 φ

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 51: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1 0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

1 1 φ

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0

Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 52: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

1 1 φ

��0/1

1/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0

Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 53: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

1 1 φ

��0/1

1/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0

Iteration: 1, |f | = 1

Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 54: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

1 φ

��0/1

1/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0

Iteration: 1, |f | = 1

Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 55: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

0/φ

s

2 3 4 5

t

1 φ

��0/1

1/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1

Iteration: 2, |f | = 1

Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 56: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

1 φ

��0/11/1

1

��0/φ��1/1��0/1

φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1

Iteration: 2, |f | = 1

Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 57: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

1 φ

��0/11/1

1

��0/φ��1/1��0/1

φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1

Iteration: 2, |f | = 1 + φ

Iteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 58: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1

φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1

Iteration: 2, |f | = 1 + φ

Iteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 59: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1

φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φ

Iteration: 3, |f | = 1 + φ

Iteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 60: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1

0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φ

Iteration: 3, |f | = 1 + φ

Iteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 61: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1

0/φ1/11− φ2/1

��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φ

Iteration: 3, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 62: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1

0/φ1/11− φ2/1

��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φ

Iteration: 3, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 63: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1

0/φ1/11− φ2/1

��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 64: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1

��0/φ��1/1����1− φ2/1

φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 65: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1

φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 66: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1

φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ

Iteration: 4, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 67: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1

φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 68: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 69: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 70: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2

Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 71: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:

After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 72: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 73: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 74: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 75: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 76: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−

Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 77: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!

|f | = 1 + 2∑∞

i=1 ϕi

≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 78: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i ≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 79: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i ≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 80: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Non-Termination of Ford-Fulkerson for Irrational Capacities

s

2 3 4 5

t

./∞ ./∞ ./∞

./∞ ./∞./∞

0/1

φ2 = 1− φ

s

2 3 4 5

t

��0/11/1

1

��0/φ��1/1��0/1 φ/φ1− φ/11− φ2/1

φ

1− φ

1− φ

φφ

φ

1− φ 1 φ

��φ/φ����1− φ/11− φ2/1 0/φ1/11− φ2/1 ��0/φ��1/1����1− φ2/1 φ− φ3/φφ/11/1

1

φ

1− φ

φ− φ3

φ3

��1/1 ��φ/1 φ− φ3/φ

1− φ2/1 1/1 φ− φ3/φ

11− φ

φ 1− φ

φ3

Iteration: 1, |f | = 0Iteration: 1, |f | = 1Iteration: 2, |f | = 1Iteration: 2, |f | = 1 + φIteration: 3, |f | = 1 + φIteration: 3, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φIteration: 4, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ φ2Iteration: 5, |f | = 1 + 2 · φ+ 2 · φ2

In summary:After iteration 1: 0←−, 1−→, 0←−, |f | = 1

After iteration 5: 1−φ2

←− , 1−→, φ−φ3

←− , |f | = 1 + 2φ+ 2φ2

After iteration 9: 1−φ4

←− , 1−→, φ−φ5

←− , |f | = 1 + 2φ+ 2φ2 + 2φ3 + 2φ4

More generally,

For every i = 0, 1, . . . after iteration 1 + 4 · i : 1−φ2i

−→ , 1−→, φ−φ2i+1

←−Ford-Fulkerson does not terminate!|f | = 1 + 2

∑∞i=1 ϕ

i ≈ 4.23607 < 5

It does not even converge to a maximum flow!

iterations

flow value

1 5 9 13 17 21 25 29 33 37 41 45 49

1

2

3

4

5

6

7

6.6: Maximum flow T.S. 16

Page 81: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Summary and Outlook

works only for integral (rational) capacities

Runtime: O(E · |f ∗|) = O(E · V · C)

Ford-Fulkerson Method

Idea: Find an augmenting path with high capacity

Consider subgraph of Gf consisting of edges (u, v) with cf (u, v) > ∆

scaling parameter ∆, which is initially 2dlog2 Ce and 1 after termination

Runtime: O(E2 · log C)

Capacity-Scaling Algorithm

Idea: Find the shortest augmenting path in Gf

Runtime: O(E2 · V )

Edmonds-Karp Algorithm

6.6: Maximum flow T.S. 17

Page 82: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Summary and Outlook

works only for integral (rational) capacities

Runtime: O(E · |f ∗|) = O(E · V · C)

Ford-Fulkerson Method

Idea: Find an augmenting path with high capacity

Consider subgraph of Gf consisting of edges (u, v) with cf (u, v) > ∆

scaling parameter ∆, which is initially 2dlog2 Ce and 1 after termination

Runtime: O(E2 · log C)

Capacity-Scaling Algorithm

Idea: Find the shortest augmenting path in Gf

Runtime: O(E2 · V )

Edmonds-Karp Algorithm

6.6: Maximum flow T.S. 17

Page 83: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Summary and Outlook

works only for integral (rational) capacities

Runtime: O(E · |f ∗|) = O(E · V · C)

Ford-Fulkerson Method

Idea: Find an augmenting path with high capacity

Consider subgraph of Gf consisting of edges (u, v) with cf (u, v) > ∆

scaling parameter ∆, which is initially 2dlog2 Ce and 1 after termination

Runtime: O(E2 · log C)

Capacity-Scaling Algorithm

Idea: Find the shortest augmenting path in Gf

Runtime: O(E2 · V )

Edmonds-Karp Algorithm

6.6: Maximum flow T.S. 17

Page 84: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Summary and Outlook

works only for integral (rational) capacities

Runtime: O(E · |f ∗|) = O(E · V · C)

Ford-Fulkerson Method

Idea: Find an augmenting path with high capacity

Consider subgraph of Gf consisting of edges (u, v) with cf (u, v) > ∆

scaling parameter ∆, which is initially 2dlog2 Ce and 1 after termination

Runtime: O(E2 · log C)

Capacity-Scaling Algorithm

Idea: Find the shortest augmenting path in Gf

Runtime: O(E2 · V )

Edmonds-Karp Algorithm

6.6: Maximum flow T.S. 17

Page 85: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Outline

A Glimpse at the Max-Flow Min-Cut Theorem

Analysis of Ford-Fulkerson

Matchings in Bipartite Graphs

6.6: Maximum flow T.S. 18

Page 86: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 87: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 88: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 89: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 90: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 91: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 92: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 93: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Application: Maximum-Bipartite-Matching Problem

A matching is a subset M ⊆ E such that for allv ∈ V , at most one edge of M is incident to v .

Matching

A graph G is bipartite if V can be partitioned into Land R so that all edges go between L and R.

Bipartite Graph

Given a bipartite graph G = (L ∪ R,E), find amatching of maximum cardinality.

L R

Jobs Machines

6.6: Maximum flow T.S. 19

Page 94: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Matchings in Bipartite Graphs via Maximum Flows

a

b

c

d

e

f

g

h

i

j

k

l

s t

6.6: Maximum flow T.S. 20

Page 95: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Matchings in Bipartite Graphs via Maximum Flows

a

b

c

d

e

f

g

h

i

j

k

l

s t

6.6: Maximum flow T.S. 20

Page 96: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Matchings in Bipartite Graphs via Maximum Flows

a

b

c

d

e

f

g

h

i

j

k

l

s t

6.6: Maximum flow T.S. 20

Page 97: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Matchings in Bipartite Graphs via Maximum Flows

a

b

c

d

e

f

g

h

i

j

k

l

s t

6.6: Maximum flow T.S. 20

Page 98: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

Correspondence between Maximum Matchings and Max Flow

The cardinality of a maximum matching M in a bipartite graph G equalsthe value of a maximum flow f in the corresponding flow network G̃.

Theorem (Corollary 26.11)

a

b

c

d

e

f

g

h

i

j

k

l

Graph G

a

b

c

d

e

f

g

h

i

j

k

l

s t

Graph G̃

6.6: Maximum flow T.S. 21

Page 99: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 100: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 101: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 102: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 103: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 104: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 105: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Matching to Flow

Given a maximum matching of cardinality k

Consider flow f that sends one unit along each each of k paths

⇒ f is a flow and has value k

max cardinality matching ≤ value of maxflow

Graph G

s t

Graph G̃

6.6: Maximum flow T.S. 22

Page 106: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value k

Integrality Theorem

⇒ f (u, v) ∈ {0, 1} and k integral

Let M ′ be all edges from L to R which carry a flow of onea) Flow Conservation

⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R

6.6: Maximum flow T.S. 23

Page 107: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value k

Integrality Theorem

⇒ f (u, v) ∈ {0, 1} and k integral

Let M ′ be all edges from L to R which carry a flow of onea) Flow Conservation

⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R

L R

6.6: Maximum flow T.S. 23

Page 108: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value k

Integrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation

⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R

L R

6.6: Maximum flow T.S. 23

Page 109: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integral

Let M ′ be all edges from L to R which carry a flow of onea) Flow Conservation

⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R

L R

6.6: Maximum flow T.S. 23

Page 110: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation

⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 111: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation

⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 112: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation

⇒ every node in L sends at most one unitb) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 113: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 114: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unit

b) Flow Conservation

⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 115: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unitb) Flow Conservation⇒ every node in R receives at most one unit

c) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 116: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unitb) Flow Conservation⇒ every node in R receives at most one unitc) Cut (L ∪ {s},R ∪ {t})

⇒ net flow is k ⇒ M ′ has k edges⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 117: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unitb) Flow Conservation⇒ every node in R receives at most one unitc) Cut (L ∪ {s},R ∪ {t})⇒ net flow is k

⇒ M ′ has k edges⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 118: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unitb) Flow Conservation⇒ every node in R receives at most one unitc) Cut (L ∪ {s},R ∪ {t})⇒ net flow is k ⇒ M ′ has k edges

⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 119: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unitb) Flow Conservation⇒ every node in R receives at most one unitc) Cut (L ∪ {s},R ∪ {t})⇒ net flow is k ⇒ M ′ has k edges⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23

Page 120: 6.6: Maximum flow - University of Cambridge · A Glimpse at the Max-Flow Min-Cut Theorem Analysis of Ford-Fulkerson Matchings in Bipartite Graphs 6.6: Maximum flow T.S. 13. Analysis

From Flow to Matching

Let f be a maximum flow in G̃ of value kIntegrality Theorem⇒ f (u, v) ∈ {0, 1} and k integralLet M ′ be all edges from L to R which carry a flow of one

a) Flow Conservation⇒ every node in L sends at most one unitb) Flow Conservation⇒ every node in R receives at most one unitc) Cut (L ∪ {s},R ∪ {t})⇒ net flow is k ⇒ M ′ has k edges⇒ By a) & b), M ′ is a matching and by c), M ′ has cardinality k

value of maxflow ≤ max cardinality matching

s t

1/1

1/1

1/1

L R L R6.6: Maximum flow T.S. 23