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A model and algorithm for multicriteria route-mode choice

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  • Dial, Robert B.

Abstract

Using an idea proposed independently by Quandt and Schneider, the paper declares mode choice to be a special instance of route choice. It describes a (non-logit) model which includes in its route-choice mechanism the decision variables traditionally associated with mode choice. With the assumption that each traveller selects the route which minimizes his own personal linear choice function, it is clear that the routes with a nonzero chance of being picked are only those not dominated by any other path (e.g. are not both costlier and longer than any other path). The precise probability of a route being chosen is just the integral over the appropriate portion of the probability density of the coefficients of the choice function. The integration limits are implied by the amount of each disutility on each of the undominated routes. An algorithm is given which is quite efficient in finding these paths in a large and complex multimodal network.

Suggested Citation

  • Dial, Robert B., 1979. "A model and algorithm for multicriteria route-mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 13(4), pages 311-316, December.
    • Handle: RePEc:eee:transb:v:13:y:1979:i:4:p:311-316
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    Cited by:

    1. Andrea Raith & Judith Wang & Matthias Ehrgott & Stuart Mitchell, 2014. "Solving multi-objective traffic assignment," Annals of Operations Research, Springer, vol. 222(1), pages 483-516, November.
    2. Steven A. Gabriel & David Bernstein, 2000. "Nonadditive Shortest Paths: Subproblems in Multi-Agent Competitive Network Models," Computational and Mathematical Organization Theory, Springer, vol. 6(1), pages 29-45, May.
    3. Xu, Zhandong & Chen, Anthony & Liu, Xiaobo, 2023. "Time and toll trade-off with heterogeneous users: A continuous time surplus maximization bi-objective user equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 31-58.
    4. Hughes, Michael S. & Lunday, Brian J. & Weir, Jeffrey D. & Hopkinson, Kenneth M., 2021. "The multiple shortest path problem with path deconfliction," European Journal of Operational Research, Elsevier, vol. 292(3), pages 818-829.
    5. Wang, Judith Y.T. & Ehrgott, Matthias, 2013. "Modelling route choice behaviour in a tolled road network with a time surplus maximisation bi-objective user equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 342-360.
    6. Giulia Reggiani & Tim Oijen & Homayoun Hamedmoghadam & Winnie Daamen & Hai L. Vu & Serge Hoogendoorn, 2022. "Understanding bikeability: a methodology to assess urban networks," Transportation, Springer, vol. 49(3), pages 897-925, June.
    7. Wang, Guangchao & Jia, Ning & Ma, Shoufeng & Qi, Hang, 2014. "A rank-dependent bi-criterion equilibrium model for stochastic transportation environment," European Journal of Operational Research, Elsevier, vol. 235(3), pages 511-529.
    8. Sune Lauth Gadegaard & Lars Relund Nielsen & Matthias Ehrgott, 2019. "Bi-objective Branch-and-Cut Algorithms Based on LP Relaxation and Bound Sets," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 790-804, October.
    9. Ehrgott, Matthias & Wang, Judith Y.T. & Watling, David P., 2015. "On multi-objective stochastic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 704-717.
    10. Opasanon, Sathaporn & Miller-Hooks, Elise, 2006. "Multicriteria adaptive paths in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 173(1), pages 72-91, August.
    11. Tao Zhang & Yang Yang & Gang Cheng & Minjie Jin, 2020. "A Practical Traffic Assignment Model for Multimodal Transport System Considering Low-Mobility Groups," Mathematics, MDPI, vol. 8(3), pages 1-19, March.
    12. Bury Alan & Paraskevadakis Dimitrios & Ren Jun & Saeed Farhan, 2017. "A framework for use in modelling the modal choice decision making process in North West England’s Atlantic Gateway," Logistics, Supply Chain, Sustainability and Global Challenges, Sciendo, vol. 8(1), pages 19-30, May.
    13. Zhang, Yuli & Shen, Zuo-Jun Max & Song, Shiji, 2016. "Parametric search for the bi-attribute concave shortest path problem," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 150-168.
    14. Dial, Robert B., 1997. "Bicriterion traffic assignment: Efficient algorithms plus examples," Transportation Research Part B: Methodological, Elsevier, vol. 31(5), pages 357-379, October.
    15. O’Neill, Sam & Bagdasar, Ovidiu & Berry, Stuart & Popovici, Nicolae & Raja, Ramachandran, 2022. "Modelling equilibrium for a multi-criteria selfish routing network equilibrium flow problem," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 658-669.
    16. Ding, Hongxing & Yang, Hai & Xu, Hongli & Li, Ting, 2023. "Status quo-dependent user equilibrium model with adaptive value of time," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 77-90.
    17. Khani, Alireza & Boyles, Stephen D., 2015. "An exact algorithm for the mean–standard deviation shortest path problem," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 252-266.
    18. Hongli Xu & Hai Yang & Jing Zhou & Yafeng Yin, 2017. "A Route Choice Model with Context-Dependent Value of Time," Transportation Science, INFORMS, vol. 51(2), pages 536-548, May.
    19. Li, Qianfei & (Will) Chen, Peng & (Marco) Nie, Yu, 2015. "Finding optimal hyperpaths in large transit networks with realistic headway distributions," European Journal of Operational Research, Elsevier, vol. 240(1), pages 98-108.
    20. Nir Halman & Mikhail Y. Kovalyov & Alain Quilliot & Dvir Shabtay & Moshe Zofi, 2019. "Bi-criteria path problem with minimum length and maximum survival probability," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 469-489, June.

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