A freight transport optimization model for integrated network, service, and policy design

This paper presents a freight transport optimization model that simultaneously incorporates multimodal infrastructure, hub-based service network structures, and the various design objectives of multiple actors. The model has been calibrated and validated using real-life data from the case study of hinterland container transport of the Netherlands, where CO2 pricing, terminal network configuration, and hub-service networks are chosen as the design measures. Policy packages combining multiple types of policies show better network performance as compared with the optimal performance resulting from a single policy type. This illustrates the value of incorporating multiple types of policies simultaneously in freight transport optimization.

[1]  Bart Jourquin,et al.  External Costs of the Belgian Interurban Freight Traffic : A Network Analysis of their Internalisation , 2002 .

[2]  Bart Jourquin,et al.  Optimal rail-road container terminal locations on the European network , 2009 .

[3]  Gerrit K. Janssens,et al.  Decision support in intermodal transport: A new research agenda , 2013, Comput. Ind..

[4]  Jean-Paul Rodrigue,et al.  Inland Terminals, Regions and Supply Chains , 2009 .

[5]  Franklin Farell Roadmap to a Single European Transport Area: Towards a competitive and resource efficient transport system , 2014 .

[6]  Lori Tavasszy,et al.  Combining Models and Commodity Chain Research for Making Long-Term Projections of Port Throughput: an Application to the HamburgLe Havre Range , 2012, European Journal of Transport and Infrastructure Research.

[7]  Johan Woxenius,et al.  Generic Framework for Transport Network Designs: Applications and Treatment in Intermodal Freight Transport Literature , 2007 .

[8]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[9]  R. Wardlaw,et al.  EVALUATION OF GENETIC ALGORITHMS FOR OPTIMAL RESERVOIR SYSTEM OPERATION , 1999 .

[10]  Lori Tavasszy,et al.  Towards collaborative, intermodal hub networks. A case study in the fast moving consumer goods market , 2005 .

[11]  W. Spears,et al.  On the Virtues of Parameterized Uniform Crossover , 1995 .

[12]  Dominic Stead,et al.  Mid-term review of the European Commissions 2001 Transport White Paper , 2006 .

[13]  Eiichi Taniguchi,et al.  A supply chain-transport supernetwork equilibrium model with the behaviour of freight carriers , 2011 .

[14]  Christopher R. Houck,et al.  A Genetic Algorithm for Function Optimization: A Matlab Implementation , 2001 .

[15]  S. Bakker,et al.  Hoofdonderzoek naar de reistijdwaardering in het vervoer van goederen over de weg , 2004 .

[16]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[17]  Harry Geerlings,et al.  A new method for assessing CO2-emissions from container terminals: a promising approach applied in Rotterdam , 2011 .

[18]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[19]  B. Jourquin,et al.  Lines and services in a regional multi-modal transport model: the case of the regional express network around Brussels , 2009 .

[20]  Teodor Gabriel Crainic,et al.  Service network design in freight transportation , 2000, Eur. J. Oper. Res..

[21]  Lino A. Costa,et al.  An elitist genetic algorithm for multiobjective optimization , 2004 .

[22]  Wpm Wim Nuijten,et al.  Multimodal freight transportation planning: A literature review , 2014, Eur. J. Oper. Res..

[23]  Ekki Kreutzberger,et al.  Distance and time in intermodal goods transport networks in Europe: A generic approach , 2008 .

[24]  John Golias,et al.  Comparative evaluation of existing and innovative rail-road freight transport terminals , 2002 .

[25]  Jun Castro,et al.  Designing Multimodal Freight Transport Networks: A Heuristic Approach and Applications , 2009, Transp. Sci..

[26]  J. Holtrop,et al.  AN APPROXIMATE POWER PREDICTION METHOD , 1982 .