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Bart JOURQUIN and Sabine LIMBOURG Catholic University of Mons (FUCAM) Group Transport & Mobility Mons – Belgium Optimal location of container.

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Presentation on theme: "Bart JOURQUIN and Sabine LIMBOURG Catholic University of Mons (FUCAM) Group Transport & Mobility Mons – Belgium Optimal location of container."— Presentation transcript:

1 Bart JOURQUIN and Sabine LIMBOURG Catholic University of Mons (FUCAM) Group Transport & Mobility Mons – Belgium gt&m@fucam.ac.be Optimal location of container terminals The case of a hub system in Europe GRT conference, May 7, 2007

2 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 12.10 9 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 policy Methodology Application Conclusions - Prospects European transport sector and policy

3 Optimal location of container terminals - The case of a hub system in Europe 3 Source : UIRR Terminals’ location = crucial Introduction: Combined rail-road transport Methodology Application Conclusions - Prospects Consolidate flows Combined rail-road transport

4 Optimal location of container terminals - The case of a hub system in Europe 4 Introduction Methology: Terminal typology Application Conclusions - Prospects T T Terminal typology Ballis (2002) Wiegmans (2003) Bontekoning and E. Kreutzberger (2001) Wiegmans, Masurel and Peter Nijkamp (1998) Daubresse (1997) SIMET (1995)

5 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 NO M L K A B C D E F J I H G Introduction Methology: Hub-and-spoke network Application Conclusions - Prospects Hub-and-spoke network

6 Optimal location of container terminals - The case of a hub system in Europe 6 Optimal terminal locations SupplyDemand Final assignment Waterways – Roads – Railways – Intermodal Introduction Methology: A four steps methodology Application Conclusions - Prospects Potential locations Reference assignment Waterways – Roads – Railways Intermodal in an Hub-and-spoke network 0 Data 1 Identification 2 P-HMP 3 H-S impact

7 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. Introduction Methology Application: Demand Conclusions - Prospects

8 Optimal location of container terminals - The case of a hub system in Europe 8 Introduction Methology Application: Demand Conclusions - Prospects

9 Optimal location of container terminals - The case of a hub system in Europe 9 Supply = DCW based network with associated transport costs Introduction Methology Application: Supply Conclusions - Prospects

10 Optimal location of container terminals - The case of a hub system in Europe 10 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Virtual networks XaXa U 1 (W2) U 3 (R1) U 2 (W1) XbXb XcXc XdXd U 1 (W2 = 1350T)) U 3 (R1 = Train) U 1 (W1 = 300T) Terminal

11 Optimal location of container terminals - The case of a hub system in Europe 11 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Virtual networks T

12 Optimal location of container terminals - The case of a hub system in Europe 12 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Virtual networks Generation Distribution Modal split Assignment Virtual Network O D

13 Optimal location of container terminals - The case of a hub system in Europe 13 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Behaviour NoYes Capacity NoAll or NothingStochastic YesEquilibriumStochastic equilibrium

14 Optimal location of container terminals - The case of a hub system in Europe 14 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Aggregated demand data NoYes Capacity NoAll or NothingMulti-Flow YesEquilibriumEquilibrium MF

15 Optimal location of container terminals - The case of a hub system in Europe 15 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Multi-modal, multi-flows assignment

16 Optimal location of container terminals - The case of a hub system in Europe 16 Introduction Methology Application: Consolidation Conclusions - Prospects Consolidated flows on road networks

17 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. Introduction Methology Application: Set of potential locations Conclusions - Prospects Set of potential locations

18 Optimal location of container terminals - The case of a hub system in Europe 18 Introduction Methology Application: Set of potential locations Conclusions - Prospects Set of potential locations

19 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 Introduction Methology Application: Hypotheses Conclusions - Prospects Hypotheses (3) (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)

20 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 Introduction Methology Application: Inter-hub networks Conclusions - Prospects Inter-hub networks

21 Optimal location of container terminals - The case of a hub system in Europe 21 Existing situation: -1,34.10 9 t.km by road Marco Polo’s objective: - 12.10 9 t.km by road Introduction Methology Application: Existing situation in 2002 Conclusions - Prospects Existing situation

22 Optimal location of container terminals - The case of a hub system in Europe 22 Introduction Methology Application: P-HMP Optimal locations Conclusions - Prospects Optimal location: -7,59.10 9 t.km by road Existing situation: -1,34.10 9 t.km by road Marco Polo’s objective: -12.10 9 t.km by road Optimal location

23 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. Introduction Methology Application Conclusions - Prospects

24 Optimal location of container terminals - The case of a hub system in Europe 24 Sensitivity analysis Trimodal terminals Short-sea shipping Introduction Methology Application Conclusions - Prospects Prospects


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