bart jourquin and sabine limbourg catholic university of mons (fucam) group transport & mobility...

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Bart JOURQUIN and Sabine LIMBOURG Catholic University of Mons (FUCAM) Group Transport & Mobility Mons – Belgium gt&[email protected] Optimal location of container terminals The case of a hub system in Europe GRT conference, May 7, 2007

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Bart JOURQUIN and Sabine LIMBOURG

Catholic University of Mons (FUCAM)

Group Transport & Mobility

Mons – Belgium

gt&[email protected]

Optimal location of container terminalsThe case of a hub system in Europe

Optimal location of container terminalsThe case of a hub system in Europe

GRT conference, May 7, 2007

Optimal location of container terminals - The case of a hub system in Europe 2

• Major problems : – congestion;– environmental nuisance;– accidents.

• Objectives:– restoring the balance between modes of transport and

developing intermodality• Marco Polo’s objective: Decrease of 12.109 t.km by road per year

– combating congestion– putting safety and the quality of services at the heart of our

efforts– maintaining the right to mobility.

Introduction: European transport sector and policyMethodology

ApplicationConclusions - Prospects

European transport sector and policy

Optimal location of container terminals - The case of a hub system in Europe 3

Source : UIRR

Terminals’ location = crucial

Introduction: Combined rail-road transportMethodology

ApplicationConclusions - Prospects

Consolidate flows

Combined rail-road transport

Optimal location of container terminals - The case of a hub system in Europe 4

IntroductionMethology: Terminal typology

ApplicationConclusions - Prospects

T T

Terminal typology•Ballis (2002) •Wiegmans (2003) •Bontekoning and E. Kreutzberger (2001)•Wiegmans, Masurel and Peter Nijkamp (1998)•Daubresse (1997)•SIMET (1995)

Optimal location of container terminals - The case of a hub system in Europe 5

• 3 constraints:– all the hubs are connected directly

to each other; – no direct connection between non-

hub nodes;– spoke nodes are connected to a

single hub.• Problem class:

P-hub Median Problem (P-HMP)– O’Kelly (1987) – Campbell (1994) – Ernst and Krishnamoorthy (1996)

• Potential location – Arnold (2002) – Macharis (2004) – New feature : Systematic

approach based on transport flows

N O

M

L

K

A

B

C

D

E

FJ

IH

G

IntroductionMethology: Hub-and-spoke network

ApplicationConclusions - Prospects

Hub-and-spoke network

Optimal location of container terminals - The case of a hub system in Europe 6

Optimal terminal locations

SupplyDemand

Final assignment Waterways – Roads – Railways – Intermodal

IntroductionMethology: A four steps methodology

ApplicationConclusions - Prospects

Potential locations

Reference assignmentWaterways – Roads – Railways

Intermodal in an Hub-and-spoke network

0 Data

1 Identification

2 P-HMP

3H-S impact

Optimal location of container terminals - The case of a hub system in Europe 7

Freight OD matrixes for the year 2000 provided by NEA

– Roads, railways and inland waterways;– NST-R chapter 9 (“diverse” commodities);– Region-to-region at NUTS 2 level;– Most European countries.

IntroductionMethology

Application: DemandConclusions - Prospects

Optimal location of container terminals - The case of a hub system in Europe 8

IntroductionMethology

Application: DemandConclusions - Prospects

Optimal location of container terminals - The case of a hub system in Europe 9

Supply = DCW based network with associated transport costs

IntroductionMethology

Application: SupplyConclusions - Prospects

Optimal location of container terminals - The case of a hub system in Europe 10

IntroductionMethology

Application: Calibrated reference scenarioConclusions - Prospects

Virtual networks

Xa

U1 (W2)

U3 (R1)

U2 (W1)

Xb Xc

Xd

U1 (W2 = 1350T))

U3 (R1 = Train)

U1 (W1 = 300T)

Terminal

Optimal location of container terminals - The case of a hub system in Europe 11

IntroductionMethology

Application: Calibrated reference scenarioConclusions - Prospects

Virtual networks

c2W1 b2W1

b1W2

b1W1 a1W1

a1W2

d3R1

b3R1

b2W1

b1W2

b1W1

b000

b3R1

+

-

+

+

-

+

-

+

-

-

T

Optimal location of container terminals - The case of a hub system in Europe 12

IntroductionMethology

Application: Calibrated reference scenarioConclusions - Prospects

Virtual networks

Generation

Distribution

Modal split

AssignmentVirtual Network

OD

Optimal location of container terminals - The case of a hub system in Europe 13

IntroductionMethology

Application: Calibrated reference scenarioConclusions - Prospects

Behaviour

No Yes

Capacity

No All or Nothing Stochastic

Yes Equilibrium Stochastic equilibrium

Optimal location of container terminals - The case of a hub system in Europe 14

IntroductionMethology

Application: Calibrated reference scenarioConclusions - Prospects

Aggregated demand data

No Yes

Capacity

No All or Nothing Multi-Flow

Yes Equilibrium Equilibrium MF

Optimal location of container terminals - The case of a hub system in Europe 15

IntroductionMethology

Application: Calibrated reference scenarioConclusions - Prospects

Multi-modal, multi-flows assignment

Optimal location of container terminals - The case of a hub system in Europe 16

IntroductionMethology

Application: ConsolidationConclusions - Prospects

Consolidated flows on road networks

Optimal location of container terminals - The case of a hub system in Europe 17

Possible criteria :– Minimum flow threshold; – Maximum distance to railways;– Minimum distance to existing terminal;– Minimum distance to port; – Maximum distance to waterways.

IntroductionMethology

Application: Set of potential locationsConclusions - Prospects

Set of potential locations

Optimal location of container terminals - The case of a hub system in Europe 18

IntroductionMethology

Application: Set of potential locationsConclusions - Prospects

Set of potential locations

Optimal location of container terminals - The case of a hub system in Europe 19

(1) Transhipment cost : 3.29 €/ton

(2) Inter-hub discount : 10%

(3) Pre- and post-haulage : 1.483 x long haul road cost

Source : UIRR

IntroductionMethology

Application: HypothesesConclusions - Prospects

Hypotheses

(3) (3)(1) (1)(2)

Collection and synthesis:•Real Cost Reduction of Door-to-door Intermodal Transport (2001)•Prospects of Inland Navigation within the enlarged Europe (2004)•Comité National Routier français •Ministère de la Mobilité des Pays-Bas (2005)

Optimal location of container terminals - The case of a hub system in Europe 20

2 terminals 3 terminals 4 terminals

5 terminals 6 terminals 7 terminals

IntroductionMethology

Application: Inter-hub networksConclusions - Prospects

Inter-hub networks

Optimal location of container terminals - The case of a hub system in Europe 21

Existing situation: -1,34.109 t.km by roadMarco Polo’s objective: -12.109 t.km by road

IntroductionMethology

Application: Existing situation in 2002Conclusions - Prospects

Existing situation

Optimal location of container terminals - The case of a hub system in Europe 22

IntroductionMethology

Application: P-HMP Optimal locationsConclusions - Prospects

Optimal location: -7,59.109 t.km by roadExisting situation: -1,34.109 t.km by roadMarco Polo’s objective: -12.109 t.km by road

Optimal location

Optimal location of container terminals - The case of a hub system in Europe 23

Major contributions:– Flow based approach;– Methodology for potential locations;– Decision support tools embedded in a GIS.

IntroductionMethology

ApplicationConclusions - Prospects

Optimal location of container terminals - The case of a hub system in Europe 24

• Sensitivity analysis

• Trimodal terminals

• Short-sea shipping

IntroductionMethology

ApplicationConclusions - Prospects

Prospects