Transport Decisions
CR (2004) Prentice Hall, Inc.
Chapter 7
If you are planning for one year, grow rice. If you are planning for 20 years, grow trees. If you are planning for centuries, grow men.
A Chinese proverb
Transport Decisions
in Transport Strategy
CR (2004) Prentice Hall, Inc.
PLANNING
ORGANIZING
CONTROLLING
Transport Strategy
Transport fundamentals
Transport decisions
Customer
service goals
The product
Logistics service
Ord
. proc. & info. sys.
Inventory Strategy
Forecasting
Inventory decisions
Purchasing and supply
scheduling decisions
Storage fundamentals
Storage decisions
Location Strategy
Location decisions
The network planning process
PLANNING
ORGANIZING
CONTROLLING
Transport Strategy
Transport fundamentals
Transport decisions
Customer
service goals
The product
Logistics service
Ord
. proc. & info. sys.
Inventory Strategy
Forecasting
Inventory decisions
Purchasing and supply
scheduling decisions
Storage fundamentals
Storage decisions
Location Strategy
Location decisions
The network planning process
Just a few of the many
problems in transportation
Typical Transport Decisions
CR (2004) Prentice Hall, Inc.
Mode/Service selection
Private fleet planning
-
Carrier routing
-
Routing from multiple points
-
Routing from coincident origin
-
destination
points
-
Vehicle routing and scheduling
Freight consolidation
Mode/Service Selection
CR (2004) Prentice Hall, Inc.
The problem
-
Define the available choices
-
Balance performance effects on inventory against
the cost of transport
Methods for selection
-
Indirectly through network configuration
-
Directly through channel simulation
-
Directly through a spreadsheet approach as f
ollows:
Alternatives
Cost types Air Truck Rail
Transportation
In
-
transit inventory
Source inventory
Destination inventory
Mode/Service Selection (Contd)
Example Finished goods are to be shipped from a plant inventory to a warehouse inventory some distance away. The expected volume to be shipped in a year is 1,200,000 lb. The product is worth $25 per lb. and the plant and carrying costs are 30% per year.
Other data are:
CR (2004) Prentice Hall, Inc.
Transport
choice
Rate,
$/lb.
Transit
time,
days
Shipment
size, lb.
Rail
0.11
25
100,000
Truck
0.20
13
40,000
Air
0.88
1
16,000
Include transport rate
Transport Selection Analysis
Cost
type
Compu-
tation
Rail
Truck
Air
Trans-
portation
RD
.11(1,200,000)
= $132,000
.20(1,200,000)
= $240,000
.88(1,200,000)
= $1,056,000
In-transit
inventory
[.30(25)
1,200,000(25)]/365
= $616,438
[.30(25)
1,200,000(13)]/365
= $320,548
[.30(25)
1,200,000(1)]/365
= $24,658
Plant
inventory
[.30(25)
100,000]/2
= $375,000
[.30(25)
40,000]/2
= $150,000
[.30(25)
16,000]/2
= $60,000
Whse
inventory
[.30(25.11)
100,000]/2
= $376,650
[.30(25.20)
40,000]/2
= $151,200
[.30(25.88)
16,000]/2
= $62,112
Totals
$1,500,088
$
861,748
$1,706,770
Improved service
CR (2004) Prentice Hall, Inc.
7-6
ICDT
365
ICQ
2
IC
'
Q
2
Carrier Routing
CR (2004) Prentice Hall, Inc.
Determine the best path betweenorigin and destination points over a network of routes
Shortest route method is efficient forfinding the minimal cost route
Consider a time network between Amarillo and Fort Worth. Find the minimum travel time.
The procedure can be paraphrased as:
Find the closest unsolved node to a solved node
Calculate the cost to the unsolved node by adding the accumulated cost to the solved node to the cost from the solved node to the unsolved node.
Select the unsolved node with the minimum time as the new solved node. Identify the link.
When the destination node is solved, the computations stop. The solution is found by backtracking through the connections made.
Carrier Routing (Contd)
Can be a weighted index of time and distance
CR (2004) Prentice Hall, Inc.
Note
: All link times are in minutes
90
Origin
Amarillo
Oklahoma
City
Destination
Fort Worth
A
B
E
I
C
D
G
F
H
J
90 minutes
84
84
138
348
156
48
132
150
126
132
120
66
126
48
60
Shortest Route Method
CR (2004) Prentice Hall, Inc.
Step
Solved
Nodes
Directly
Connected
to Unsolved
Nodes
Its
Closest
Connected
Unsolved
Node
Total Cost
Involved
nth
Nearest
Node
Its
Minimu
m Cost
Its Last
Connection
a
1
A
B
90
B
90
AB
*
2
A
C
138
C
138
AC
B
C
90+66=156
3
A
D
348
B
E
90+84=174
E
174
BE
*
C
F
138+90=228
4
A
D
348
C
F
138+90=228
F
228
CF
E
I
174+84=258
5
A
D
348
C
D
138+156=294
E
I
174+84=258
I
258
EI
*
F
H
228+60=288
6
A
D
348
C
D
138+156=294
F
H
228+60=
288
H
288
FH
I
J
258+126=384
7
A
D
348
C
D
138+156=294
D
294
CD
F
G
288+132=360
H
G
288+48=336
I
J
258+126=384
8
H
J
288+126=414
I
J
258+126=384
J
384
IJ
*
MAPQUEST SOLUTION
Mapquest at www.mapquest.com
CR (2004) Prentice Hall, Inc.
Routing from Multiple Points
This problem is solved by the traditional transportation method of linear programming
CR (2004) Prentice Hall, Inc.
Plant 1
Requirements = 600
Plant 2
Requirements = 500
Plant 3
Requirements = 300
Supplier A
Supply 400
Supplier C
Supply 500
Supplier B
Supply 700
4
a
a
The transportation rate in $ per ton for an optimal routing between supplier A and plant 1
.
7
6
5
5
5
9
5
8
TRANLP problem setup
Solution
CR (2004) Prentice Hall, Inc.
Routing with a Coincident Origin/Destination Point
CR (2004) Prentice Hall, Inc.
Typical of many single truck routing problems from a
single depot.
Mathematically, a complex problem to solve efficiently.
However, good routes can be found by forming a route
pattern where the paths do not cross
a "tear drop"
pattern.
D
D
Depot
Depot
(a) Poor routing--
paths cross
(b) Good routing--
no paths cross
Single Route Developed by ROUTESEQ in LOGWARE
0 1 2 3 4 5 6 7 8
8
7
6
5
4
3
2
1
0
X coordinates
1
2
3
19
11
12
13
14
15
16
17
18
4
5
6
7
8
9
10
20
D
Y coordinates
0 1 2 3 4 5 6 7 8
8
7
6
5
4
3
2
1
0
X coordinates
1
2
3
19
11
12
13
14
15
16
17
18
4
5
6
7
8
9
10
20
D
Y coordinates
CR (2004) Prentice Hall, Inc.
7-14
(a) Location of beverage accounts
and distribution center (D) with
grid overlay
(b) Suggested routing pattern
Multi-Vehicle Routing and Scheduling
CR (2004) Prentice Hall, Inc.
A problem similar to the single-vehicle routing problem except that a number of restrictions are placed on the problem. Chief among these are:
- A mixture of vehicles with different capacities
- Time windows on the stops
- Pickups combined with deliveries
-Total travel time for a vehicle
Practical Guidelines for Good Routing and Scheduling
1. Load trucks with stop volumes that are in closest proximity to each other
(a) Weak clustering
Depot
(b) Better clustering
CR (2004) Prentice Hall, Inc.
D
Depot
D
Stops
Guidelines (Contd)
2. Stops on different days should be arranged to produce tight clusters
May need to coordinate with sales to achieve clusters
CR (2004) Prentice Hall, Inc.
D
Depot
D
Depot
F
F
F
F
F
T
T
T
F
T
F
T
T
T
(a) Weak clustering--
routes cross
F
F
F
F
F
F
F
T
T
T
T
T
T
T
(b) Better clustering
Stop
Guidelines (Contd)
3. Build routes beginning with the farthest stop from the depot
4. The stop sequence on a route should form a teardrop pattern (without time windows)
5. The most efficient routes are built using the largest vehicles available first
6. Pickups should be mixed into delivery routes rather than assigned to the end of the routes
7. A stop that is greatly removed from a route cluster is a good candidate for an alternate means of delivery
8. Narrow stop time window restrictions should be avoided (relaxed)
Application of Guidelines to Casket Distribution
Typical weekly demand and pickups
CR (2004) Prentice Hall, Inc.
Warehouse
Funeral home
Application of Guidelines to Casket Distribution (Contd)
Division of sales territories into days of the week
Territories of
equal size
to minimize
number of trucks
CR (2004) Prentice Hall, Inc.
Warehouse
Funeral home
Application of Guidelines to Casket Distribution (Contd)
Route design within territories
CR (2004) Prentice Hall, Inc.
Warehouse
Funeral home
Sweep Method for VRP
Example A trucking company has 10,000-unit vans for merchandise pickup to be consolidated into larger loads for moving over long distances. A days pickups are shown in the figure below. How should the routes be designed for minimal total travel distance?
CR (2004) Prentice Hall, Inc.
Depot
1,000
2,000
3,000
2,000
4,000
2,000
3,000
3,000
1,000
2,000
2,000
2,000
Stop Volume and Location
CR (2004) Prentice Hall, Inc.
Geographical
region
Pickup
points
Sweep direction
is arbitrary
Depot
1,000
2,000
3,000
2,000
4,000
2,000
3,000
3,000
1,000
2,000
2,000
2,000
Sweep Method Solution
CR (2004) Prentice Hall, Inc.
Route #1
10,000 units
Route #2
9,000 units
Route #3
8,000 units
The Savings Method for VRP
Depot
Depot
(a) Initial routing
Route distance = d
0,A
+d
A,0
+d
0,B
+ d
B,0
(b) Combining two stops on a route
Route distance = d
0,A
+d
A,B
+d
B,0
A
B
A
B
Stop
Stop
0
0
Savings is better than Sweep methodhas lower average error
CR (2004) Prentice Hall, Inc.
7-25
d
A,0
d
0,A
d
0,B
d
B,0
d
B,0
d
0,A
d
A,B
Savings Method Observation
The points that offer the greatest savings when combined on the same route are those that are farthest from the depot and that are closest to each other.
This is a good principle
for constructing multiple-stop
routes
CR (2004) Prentice Hall, Inc.
Route Sequencing in VRP
8
9
10
11
12
1
2
3
4
5
6
Route #1
Route #10
AM
PM
Route #6
Route #9
Route #4
Route #5
Route #8
Route #2
Route #7
Route #3
Truck #1
Truck #2
Truck #3
Truck #4
Truck #5
Minimize number of trucks
by maximizing number of routes
handled by a single truck
CR (2004) Prentice Hall, Inc.
7-27
Freight Consolidation
Combine small shipments into larger onesA problem of balancing cost savings against customer service reductionsAn important area for cost reduction in many firmsBased on the rate-shipment size relationship for for-hire carriersCR (2004) Prentice Hall, Inc.
Freight Consolidation Analysis
CR (2004) Prentice Hall, Inc.
Suppose we have the following orders for the next three days.
Consider shipping these orders each day or consolidating them into one shipment. Suppose that we know the transport rates.
Note: Rates from an interstate tariff
From:
Ft Worth
Day 1
Day 2
Day 3
To:
Topeka
5,000 lb.
25,000 lb.
18,000 lb.
Kansas City
7,000
12,000
21,000
Wichita
42,000
38,000
61,000
Freight Consolidation Analysis (Contd)
Separate shipments
CR (2004) Prentice Hall, Inc.
7-30
Day 1
Day 2
Rate x volume = cost
Rate x volume = cost
Topeka
3.42 x 50 = $171.00
1.14 x 250 = $285.00
Kansas City
3.60 x 70 = 252.00
1.44 x 120 = 172.80
Wichita
0.68 x 420 =
285.60
0.68 x 400
a
=
272.00
Total $708.60
Total $729.80
a Ship 380 cwt., as if full truckload of 400 cwt.
Day 3
Totals
Rate x volume = cost
Topeka
1.36 x 180 = $244.80
$700.80
Kansas City
1.20 x 210 = 252.00
676.80
Wichita
0.68 x 610 =
414.80
972.40
Total $911.60
$2,350.00
Freight Consolidation Analysis (Contd)
a 480 = 50 + 250 + 180
Computing transport cost for one combined, three-day shipment
Cheaper, but what about
the service effects of holding
early orders for a longer time
to accumulate larger shipment
sizes?
Consolidated shipment
Day 3
Rate x volume = cost
Topeka
0.82 x 480
a
= $393.60
Kansas City
0.86 x 400 = 344.00
Wichita
0.68 x 1410 =
958.80
Total
$1,696.40
CR (2004) Prentice Hall, Inc.
7-31
Determine the best path between origin and destination points over a
network of routes
Shortest route method is efficient for finding the minimal cost route
Consider a time network between Amarillo and Fort Worth. Find the
minimum travel time.
The procedure can be paraphrased as:
Find the closest unsolved node to a solved node
Calculate the cost to the unsolved node by adding the accumulated
cost to the solved node to the cost from the solved node to the
unsolved node.
Select the unsolved node with t he minimum time as the new solved
node. Identify the link.
When the destination node is solved, the computations stop. The
solution is found by backtracking through the connections made.
A problem similar to the single -vehicle routing
problem except that a number of restrictions are
placed on the problem. Chief among these are:
- A mixture of vehicles with different capacities
- Time windows on the stops
- Pickups combined with deliveries
- Total travel time for a vehicle
D
D
Depot
Depot
(a) Poor routing--
paths cross
(b) Good routing--
no paths cross
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