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Colored-Edge Graph Approach for the Modeling of Multimodal Transportation Systems

Author

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  • Andrew Ensor

    (School of Computing and Mathematical Sciences, Auckland University of Technology, 2-14 Wakefield St, Auckland 1010, New Zealand)

  • Felipe Lillo

    (School of Management and Economics, Universidad CatĂłlica del Maule, Avda. San Miguel 3605, Talca, Chile)

Abstract

Many networked systems involve multiple modes of transport. Such systems are called multimodal, and examples include logistic networks, biomedical phenomena and telecommunication networks. Existing techniques for determining minimal paths in multimodal networks have either required heuristics or else application-specific constraints to obtain tractable problems, removing the multimodal traits of the network during analysis. In this paper weighted colored-edge graphs are introduced for modeling multimodal networks, where colors represent the modes of transportation. Minimal paths are selected using a partial order that compares the weights in each color, resulting in a Pareto set of minimal paths. Although the computation of minimal paths is theoretically intractable and đť’©đť’«-complete, the approach is shown to be tractable through experimental analyses without the need to apply heuristics or constraints.

Suggested Citation

  • Andrew Ensor & Felipe Lillo, 2016. "Colored-Edge Graph Approach for the Modeling of Multimodal Transportation Systems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(01), pages 1-21, February.
    • Handle: RePEc:wsi:apjorx:v:33:y:2016:i:01:n:s0217595916500056
    DOI: 10.1142/S0217595916500056
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    References listed on IDEAS

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    1. Lozano, Angélica & Storchi, Giovanni, 2002. "Shortest viable hyperpath in multimodal networks," Transportation Research Part B: Methodological, Elsevier, vol. 36(10), pages 853-874, December.
    2. Androutsopoulos, Konstantinos N. & Zografos, Konstantinos G., 2009. "Solving the multi-criteria time-dependent routing and scheduling problem in a multimodal fixed scheduled network," European Journal of Operational Research, Elsevier, vol. 192(1), pages 18-28, January.
    3. KiesmĂĽller, G.P. & de Kok, A.G. & Fransoo, J.C., 2005. "Transportation mode selection with positive manufacturing lead time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(6), pages 511-530, November.
    4. Daeki Kim & Cynthia Barnhart & Keith Ware & Gregory Reinhardt, 1999. "Multimodal Express Package Delivery: A Service Network Design Application," Transportation Science, INFORMS, vol. 33(4), pages 391-407, November.
    5. Lozano, Angelica & Storchi, Giovanni, 2001. "Shortest viable path algorithm in multimodal networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 225-241, March.
    6. Horn, Mark E. T., 2003. "An extended model and procedural framework for planning multi-modal passenger journeys," Transportation Research Part B: Methodological, Elsevier, vol. 37(7), pages 641-660, August.
    7. Byung Kim & Wonkyu Kim, 2006. "An equilibrium network design model with a social cost function for multimodal networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 40(3), pages 473-491, August.
    8. Matthias MĂĽller-Hannemann & Karsten Weihe, 2006. "On the cardinality of the Pareto set in bicriteria shortest path problems," Annals of Operations Research, Springer, vol. 147(1), pages 269-286, October.
    9. Clímaco, João C.N. & Eugénia Captivo, M. & Pascoal, Marta M.B., 2010. "On the bicriterion - minimal cost/minimal label - spanning tree problem," European Journal of Operational Research, Elsevier, vol. 204(2), pages 199-205, July.
    10. Kitamura, Ryuichi & Chen, Cynthia & Chen, Jiayu, 1999. "Daily Activity and Multimodal Travel Planner: Phase II Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5354w222, Institute of Transportation Studies, UC Berkeley.
    11. Nagurney, Anna B., 1984. "Comparative tests of multimodal traffic equilibrium methods," Transportation Research Part B: Methodological, Elsevier, vol. 18(6), pages 469-485, December.
    12. Macharis, C. & Bontekoning, Y. M., 2004. "Opportunities for OR in intermodal freight transport research: A review," European Journal of Operational Research, Elsevier, vol. 153(2), pages 400-416, March.
    13. Modesti, Paola & Sciomachen, Anna, 1998. "A utility measure for finding multiobjective shortest paths in urban multimodal transportation networks," European Journal of Operational Research, Elsevier, vol. 111(3), pages 495-508, December.
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