integrated decision support tool for intermodal freight

NECTAR Logistics and Freight cluster meeting 27/28 March 2008 Delft, the Netherlands

INTEGRATED DECISION SUPPORT TOOL FOR INTERMODAL FREIGHT TRANSPORT

Outline §  Introduction §  Assessment framework §  Description of the models §  NODUS §  LAMBIT §  SIMBA

§  Integration of the models

§  Policy measures §  Policies in Belgium §  DSSITP framework §  Costs §  Infrastructure §  Services

§  Conclusions 27/28 March 2008

NECTAR Logistics and Freight cluster meeting Slide 2

Context DSSITP: Decision support system for intermodal transport policy Transport and Logistics Research Group (MOSI-T) Vrije Universiteit Brussel Prof Cathy Macharis Ethem Pekin http://www.vub.ac.be/MOSI/ Transportation Research Institute (IMOB) Universiteit Hasselt Prof Gerrit Janssens An Caris http://www.imob.uhasselt.be The research group "Transport & Mobility“ (GTM) Facultés Universitaires Catholiques de Mons Prof Bart Jourquin Thomas Crépin http://www.fucam.ac.be/gtm

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Introduction INTERMODAL POLICIES

a further imbalance in modal split

The growth of freight transport

DSSITP 27/28 March 2008


§  Assessment framework §  Description of the models §  NODUS §  LAMBIT §  SIMBA

§  Integration of the models

Nodus – Methodology §  Model for strategic multimodal freight transportation (road, rail and inland waterways) §  Based on a Geographic Information System (GIS) §  Assessment of the modal split of goods for the different origins and destinations (O-D) §  Based on the virtual networks 27/28 March 2008


Nodus – Inputs (1) §  European geographic networks for road, rail and inland waterways plus ferry lines

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Nodus – Inputs (2) §  Origin-Destination (O-D) matrixes at NUTS5 level for Belgium and NUTS2 level for the rest of EU for 2000 §  Costs functions based on previous work by GTM for 2000 §  O-D and costs both done for each NST-R chapter §  Work based on NST-R chapter 9 27/28 March 2008


Nodus – Outputs §  Generalized costs along transportation chain for each O-D pair §  Potential optimal locations for new multimodal terminals on the inland waterways network

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LAMBIT: Methodology Fixed costs

Variable costs

§  The §  The §  The §  The 27/28 March 2008

road network inland waterways network rail network end haulage network

§  Port of Antwerp §  Inland terminals §  589 municipalities


Methodology Intermodal cost structure: •  lower variable costs •  higher fixed costs

•  The market price function •  Shortest path algorithm* •  Simulations are run •  Comparisons in Spreadsheet •  Market potential visualizations in ArcGis *In ARCINFO the algorithm of Dijkstra is used 27/28 March 2008


Inputs §  Network layers (roads, railways and inland waterways) which are obtained from the maps of TELE ATLAS and ESRI). §  The origin-destination matrices that define the port of Antwerp, the inland terminals and final destinations of the municipality centers. §  Transportation prices which are uploaded in the network layers and nodes. §  The statistics of National Institute of Statistics (NIS) which show the container transportation between the port of Antwerp and the municipalities.

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Outputs §  The current intermodal terminal landscape of Belgium is depicted. §  Simulation of location scenarios: the introduction of new intermodal terminals into the network. §  Simulation of pricing scenarios: the introduction of subsidies, internalization of external costs. §  Conducting ex-ante and ex-post analysis. §  Market area of the terminals §  Market potential of the terminals

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Case: Narcon network

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Current terminal landscape

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Future scenario: Terminal Genk and Bierset

Changes in the market areas of the terminals in Meerhout and Renory are seen as a result of the common market area. 27/28 March 2008


Subsidy Scenario:

Without a subsidized rail transport

The market areas for the Narcon terminals decrease, as the subsidy on rail transport is eliminated. 27/28 March 2008


SIMBA §  Discrete event Simulation model for InterModal BArge transport §  Hinterland waterway network of Port of Antwerp in Belgium §  Strategic decision level §  Simulate policies §  Identify bottlenecks §  Analyze future scenarios

§  Arena simulation software 27/28 March 2008


Transport network

Origins: §  Albert canal §  Upper-Sea Scheldt §  Sea canal BrusselsScheldt

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Port area Destinations §  Antwerp: right river bank §  Antwerp: left river bank §  Rotterdam §  Amsterdam §  Zeebrugge

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Conceptual model §  Components Inland waterway network

Port area Antwerp

- Terminals

Rotterdam

Amsterdam

- Waterways

Zeebrugge

- Container flows

Lock planning

§  Entities 27/28 March 2008


Assumptions §  Focus on inland waterway network -> no rail connections §  Homogeneous container type §  Equal handling time for each container §  Small waterways without inland terminals not in model §  Stochastic sailing times §  Stochastic lockage times

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Data Requirements §  Data collection inland terminals: real data input on shuttle services §  §  §  § 

Type of barge Destinations serviced Average number of import and export containers for each destination Turnaround time (validation)

§  Data collection waterway administrators

§  Non-containerized goods ->waiting times at locks §  Network connections §  §  §  §  § 

Number of locks and lock chambers Distances between locks Average lockage times Size of lock chambers Average waiting times at locks (validation)

§  Data collection port authority

§  Choice of locks in port area §  Quay length §  Average mooring time and loading / unloading time

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Outputs Shuttles Lock s

turnaround time total number waiting number waiting in queue waiting time in queue Port area number waiting in queue waiting time in queue Capacity utilization quay length network connections

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Link with assessment framework §  Policy measures affecting intermodal transport by barge §  Impact of volume increases on the network §  Future bottlenecks (locks, canals, terminals)

§  Ex-ante analysis of consolidation strategies §  Interaction effects in container flows

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Assessment framework

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§  Policy measures §  Policy measures in Belgium §  Inland waterways §  Rail

§  DSSITP framework §  Costs §  Infrastructure §  Services

Policy measures in Belgium Inland waterways

§  §  §  §  §  § 

Increase of the capacity of the inland waterways network (bottlenecks) Development of intelligent transport systems (RIS systems) A systematic maintenance of the infrastructure Port investments Stimulation of barge transport

§  §  §  §  §  § 

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PPS program Reduction of canal-dues The support of companies with their logistical choice Development of business sites Subsidy for the development of container line services in Wallonia Investment premiums for the development of barge transport/fleet in Wallonia


Policy measures in Belgium Rail

§  §  § 

Liberalization of the inland waterways sector, minor role Financial aid to rail/road intermodal transport

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DSSITP framework Categories

Policy measures Subsidy Internalization of the external costs COSTS Taxes and pricing Decrease in canal dues Public private partnerships and new terminals Capacity increase INFRASTRUCTURE Intermodal network Standardisation of the transport units Frequency Broadening of working hours SERVICES Consolidation strategy Intelligent transport systems 27/28 March 2008


SUBSIDIES

Costs NODUS • Cost functions • Modal split SIMBA • Bottlenecks • Capacity utilization LAMBIT • Market prices • Market areas

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Infrastructure NODUS

LAMBIT • Market areas • Market potentials

volumes

optimal location

• P-HMP

SIMBA • Impact on the infrastructure network

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HUB LOCATION

Services

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SIMBA • Turnaround time • Efficiency

LAMBIT • Market areas • Market potentials


Conclusions §  Model specific research: §  Data update §  Development of the models and simulations

§  Integration of the models by simulating policy measures §  Validation of the assessment framework

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Thank you! Thank you for your listening.

DSSITP research team

27/28 March 2008
