GRT conference, May 7, 2007 Optimal location of container terminals The case of a hub system in Europe Bart JOURQUIN and Sabine LIMBOURG Catholic University of Mons (FUCAM) Group Transport & Mobility Mons – Belgium gt&[email protected] Introduction: European transport sector and policy Methodology Application Conclusions - Prospects European transport sector and policy • 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. Optimal location of container terminals - The case of a hub system in Europe 2 Introduction: Combined rail-road transport Methodology Application Conclusions - Prospects Combined rail-road transport Consolidate flows Source : UIRR Terminals’ location = crucial Optimal location of container terminals - The case of a hub system in Europe 3 Introduction Methology: Terminal typology Application Conclusions - Prospects Terminal typology •Ballis (2002) •Wiegmans (2003) •Bontekoning and E. Kreutzberger (2001) •Wiegmans, Masurel and Peter Nijkamp (1998) •Daubresse (1997) •SIMET (1995) T T Optimal location of container terminals - The case of a hub system in Europe 4 Introduction Methology: Hub-and-spoke network Application Conclusions - Prospects Hub-and-spoke network N M • – all the hubs are connected directly to each other; – no direct connection between nonhub nodes; – spoke nodes are connected to a single hub. O K B C • A D L J I • G H Problem class: P-hub Median Problem (P-HMP) – O’Kelly (1987) – Campbell (1994) – Ernst and Krishnamoorthy (1996) E F 3 constraints: Potential location – Arnold (2002) – Macharis (2004) – New feature : Systematic approach based on transport flows Optimal location of container terminals - The case of a hub system in Europe 5 Introduction Methology: A four steps methodology Application Conclusions - Prospects Reference assignment Waterways – Roads – Railways Demand Supply 0 Data 1 Potential locations Optimal terminal locations Identification 2 P-HMP Intermodal in an Hub-and-spoke network 3 Final assignment Waterways – Roads – Railways – Intermodal H-S impact Optimal location of container terminals - The case of a hub system in Europe 6 Introduction Methology Application: Demand Conclusions - Prospects 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. Optimal location of container terminals - The case of a hub system in Europe 7 Introduction Methology Application: Demand Conclusions - Prospects Optimal location of container terminals - The case of a hub system in Europe 8 Introduction Methology Application: Supply Conclusions - Prospects Supply = DCW based network with associated transport costs Optimal location of container terminals - The case of a hub system in Europe 9 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Virtual networks U1 (W2) Xa U2 (W1) Xb Xc U3 (R1) Xd Terminal U1 (W2 = 1350T)) U1 (W1 = 300T) U3 (R1 = Train) Optimal location of container terminals - The case of a hub system in Europe 10 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Virtual networks a1W1 b1W1 a1W2 b1W2 T b2W1 c2W1 b3R1 - d3R1 b1W1 b1W2 b000 + + - - + b2W1 + + - b3R1 Optimal location of container terminals - The case of a hub system in Europe 11 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Virtual networks O D Generation Distribution Modal split Virtual Network Assignment Optimal location of container terminals - The case of a hub system in Europe 12 Introduction Methology Application: Calibrated reference scenario Conclusions - 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 13 Introduction Methology Application: Calibrated reference scenario Conclusions - 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 14 Introduction Methology Application: Calibrated reference scenario Conclusions - Prospects Multi-modal, multi-flows assignment Optimal location of container terminals - The case of a hub system in Europe 15 Introduction Methology Application: Consolidation Conclusions - Prospects Consolidated flows on road networks Optimal location of container terminals - The case of a hub system in Europe 16 Introduction Methology Application: Set of potential locations Conclusions - Prospects Set of potential locations Possible criteria : – – – – – Minimum flow threshold; Maximum distance to railways; Minimum distance to existing terminal; Minimum distance to port; Maximum distance to waterways. Optimal location of container terminals - The case of a hub system in Europe 17 Introduction Methology Application: Set of potential locations Conclusions - Prospects Set of potential locations Optimal location of container terminals - The case of a hub system in Europe 18 Introduction Methology Application: Hypotheses Conclusions - Prospects 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) Hypotheses (1) Transhipment cost : 3.29 €/ton (2) Inter-hub discount : 10% (3) Pre- and post-haulage : 1.483 x long haul road cost (3) (1) (2) (1) (3) Source : UIRR Optimal location of container terminals - The case of a hub system in Europe 19 Introduction Methology Application: Inter-hub networks Conclusions - Prospects Inter-hub networks 2 terminals 3 terminals 4 terminals 5 terminals 6 terminals 7 terminals Optimal location of container terminals - The case of a hub system in Europe 20 Introduction Methology Application: Existing situation in 2002 Conclusions - Prospects Existing situation Existing situation: -1,34.109 t.km by road Marco Polo’s objective: -12.109 t.km by road Optimal location of container terminals - The case of a hub system in Europe 21 Introduction Methology Application: P-HMP Optimal locations Conclusions - Prospects Optimal location Optimal location: -7,59.109 t.km by road Existing situation: -1,34.109 t.km by road Marco Polo’s objective: -12.109 t.km by road Optimal location of container terminals - The case of a hub system in Europe 22 Introduction Methology Application Conclusions - Prospects Major contributions: – Flow based approach; – Methodology for potential locations; – Decision support tools embedded in a GIS. Optimal location of container terminals - The case of a hub system in Europe 23 Introduction Methology Application Conclusions - Prospects Prospects • Sensitivity analysis • Trimodal terminals • Short-sea shipping Optimal location of container terminals - The case of a hub system in Europe 24
© Copyright 2026 Paperzz