Optimisation of Urban Freight Systems by strategic co-operations … · 2013. 11. 6. · 4...

Approaches and ToolsApproaches and Tools

Optimisation of Urban Freight Systems by strategic co-operations

Vienna, 21 September 2006Optimisation of Urban Freight Systems by strategic co-operations2

First traffic jam in the Netherlands: 1955First traffic jam in the Netherlands: 1955

Utrecht, 1955: 50.000 → 2006: 350.000 vehicles/day


Impact of restrictions on costsImpact of restrictions on costs

Gemiddelde kosten per rolcontainer voor Filiaal in het Centrum

5.4

7.5

0

1

2

3

4

5

6

7

8

9

Gemiddelde kostprijs per rolcontainer filiaal inKernwinkelgebied

Kostprijs per rolcontainer exclusiefvenstertijden in het Kernwinkelgebied

Eur

o/R

olco

ntai

ner

Average costs per rolling container forstore in city centre

with restrictions without restrictions

Dutch retail:€ 425 million/yearDutch retail:Dutch retail:€ 425 € 425 million/yearmillion/year


Regulation per municipality in the NetherlandsRegulation per municipality in the Netherlands

no time windows or vehicle restrictionsvehicle restrictionstime windowstime windows and vehicle restrictions

• over 16 million inhabitants• 180.000 shops/retail outlets• 5300 supermarkets• 53% of cities have Time Windows• 43% have Vehicle Restrictions• 59% have Restricted Access to Center

of which 21% permanent• 6,800,000 cars• 760,000 vans• 165,000 trucks


Distribution of the deliveries over the day (as percentage of the total number of consignments in 24 hours)

17.7%

1.6% 2.7%

12.6%

0.1%

65.2%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

06:00-11:00 11:00-18:00 18:00-21:00 23:00-06:00 variable unknown

The situation todayThe situation today

• Peak in capacity needed• Partially Self induced by retail• Congestion • Personnel present at stores

Tilburg, Amsterdam, Breda, Utrecht, RotterdamLeiden, Den Haag, OosterhoutGroningen, LeeuwardenDen Bosch


Recent surveyRecent survey

What is the impact of municipal regulation regarding city What is the impact of municipal regulation regarding city distribution of cargo on vehicle kilometres and fleet size?distribution of cargo on vehicle kilometres and fleet size?

• Different scenarios• Data of:

• 20 chains of supermarkets (2249 st, 35 dc)• 3 chains of department stores (328 st, 5 dc)• 4 chains of drugstores (1777 st, 5 dc)• 4 chains of electronic equipment stores (285 st, 6 dc)

• Per DC and store:• locations, opening hours, volumes, time windows, frequency,

vehicle restrictions, road network, vehicle characteristics


Stores and DC’sStores and DC’s

Each chain has stores in municipalities of all restriction types!Each chain has stores in municipalities of all restriction typesEach chain has stores in municipalities of all restriction types!! Synergy potential between DCs not used! > separate networksSynergy potential between Synergy potential between DCsDCs not used! > separate networksnot used! > separate networks


The Hague The Hague


Integrative modeling approachIntegrative modeling approach

Network designand optimization

Cost calculation Evaluation of thenetwork design

Network design ABC module Simulation module

1 2 3

Validation of the designand robustness

StrategicStructure and alignment

of the networkFacility locationInventory managementTransporation

OperationalScheduling and resource

managementSimulation techniquesVehicle RoutingScheduling

RESPONSETM

Network Design and Optimization Suite


Model usedModel used

• Vehicle routing problem with time windows (VRPTW)

• To complex for exact solution > heuristic approach

• Based on genetic algorithm of Homberger and Gehring (1999)

• Minimise costs (time or distance) delivering all customers within restrictions

( )( )( )( ) ( )

( ) ( )( )

∑ ∑

∑

= =+

=

⋅

+

−

+⋅+⋅

NofRoutes

r

rrsInRouteNofCustome

cc,rroute,c,rroute

NofRoutes

r depotID,rrsInRouteNofCustome,rroute

distancecpkm

,rleavetimetraveltimerrsInRouteNofCustome,rleavetime

cphNofRoutescpr

1 01

10


Overview of scenariosOverview of scenarios

NoYesSequential8 Local sequential time windows

NoYesWide7 National uniform wide time window

NoYesYes and No6 Only time windows in big cities

Realistic scenarios:

YesYesYes5 Impact of municipal regulation

YesNoYes4 Impact of time windows

YesYesNo3 Impact vehicle restrictions

NoNoNo2 Impact in night distribution

YesNoNo1 No restrictions

Theoretical scenarios:Theoretical scenarios:

NoYesYesCurrent situation

In night distributionVehicle RestrictionsTime WindowsScenario


VisualiserVisualiser

RandstadRandstad

Convince chain partners by showing the differences between scenarios in a way they understand!Most of the time, they are not mathematicians!

Convince chain partners by showing the differences between scenarios in a way they understand!Most of the time, they are not mathematicians!


Results Results (1)(1)

138203Cities > 50.000

135168National uniform time window

140211Regional sequential time window

143182Municipal regulation

111128Time windows

137136Vehicle restrictions

97124No In night distribution

215.000 = 100388 = 100No Restrictions

141218Current situation

KilometresFleet


Flee

tFl

eet

Kilo

met

res

(*10

00)

Kilo

met

res

(*10

00)

current

current




Length time window (hours)

Kilo

met

res

(*10

00)

F

leet

4,74,7

6%!



-39%-63%Electronic equipment stores

-33%-42%Drug stores

-43%-67%Department stores

-20%-53%Supermarkets

KilometresFleetImpact of restrictions



Regional partial sequential time windows: hardly any impact!

• In general not much regional routes but optimal spread of drops

• Optimal sequence different per chain of stores or suppliers

• Trucks used whole day: combination with no-time window areas

• Reason why increase of fleet is caused by trucks, not by vans

• Balance vehicle capacity and optimal trip length (driver shifts)

• Density of time window zones too low

• Only for regional chains of stores in an area with high density of cities with time windows

• Full sequential in bigger area (morning/afternoon)

• Bundling via city distribution centre


ConclusionsConclusions

• Regional tuning of small time windows gives no improvements

• Impact of municipal regulation mainly depends on length of time windows; a small increase shows already benefits without additional disadvantages

• Small time windows deliver local improvement on liveability but deterioration on national scale due to increase of fleet and kilometres

• Different focus/scale of chains of stores and municipalities cause at the end only negative impact of regulations (one full network versus relevant parts of all networks)

• Bundling of several suppliers in one truck seems to be the only way out


Time windowsVehicle restrictions

E

Retail warehouse

Fresh/Apparel/FoodNon-Food

Finished product incity box

Outlet in city center

S

Supermarket/outlet/store/consumer

Time windowsVehicle restrictions

An alternative using the CityAn alternative using the City--BoxBox

• Current situation in 53% of Dutch cities

E

Retail warehouse


Finished productS

Outlet in urban area

S

Supermarket/outlet/store/consumerSmall trucks due to restrictions

Peak in before 11:00 amLoss of capacity during the rest of the day

• Structure using the city-box

Crossdocklocation



E

Retail warehouse


Finished product incity box

Outlet in city center

S

Supermarket/outlet/store/consumer

Crossdocklocation



• City box standard loading unit• 2.25x2.55x2.25 meters• rolling containers, pallets, boxes and racks• lift-rolling

• minimizing the handling on crossdock• standardization city-box• standardization of vehicles


VisualiserVisualiser

TilburgTilburg


Impact of noise / emissionImpact of noise / emission


Impact of CityImpact of City--Box on kilometres, routes and Box on kilometres, routes and emissionemission

Emissies Tilburg

13

9

0

20

40

60

80

100

120

Huidige situatie Inzet stadsbox optie 1 Inzet stadsbox optie 2 Totaal effectN

O2

emission

Totaal Emissies Tilburg

3

9

0

20

40

60

80

100

120

Huidige situatie Huidige dataset Totaal aantal rittengeschat

Totaal effect

NO

2

routes

Vrachtwagenkilometers Tilburg

54007

62286

0

100,000

200,000

300,000

400,000

500,000

600,000

Huidige situatie Inzet stadsbox optie 1 Inzet stadsbox optie 2 Totaal effect

vrac

htw

agen

kilo

met

ers

per

jaar

kilometres


ConclusionsConclusions

• Less routes due to increased load factor• Reduction of kilometres mainly on line hauls\• Further improvement:

• Frequency• Drop size• Time windows• Vehicle restrictions• Improvement car technology


More information?More information?

G.W. (Egbert) Guis MScTNOBU Mobility & Logistics

[email protected]/logistiek+31 15 269 6831

Optimisation of Urban Freight Systems by strategic co-operations … · 2013. 11. 6. · 4...

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