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Combined Gravity Model Trip Distribution and Paired Combinatorial Logit Stochastic User Equilibrium Problem

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  • Ampol Karoonsoontawong
  • Dung-Ying Lin

Abstract

The equivalent mathematical formulation of the combined doubly-constrained gravity-based trip distribution and paired-combinatorial-logit stochastic user equilibrium assignment problem (CDA-PCL-SUE) is proposed. Its first order conditions are shown to be equal to the gravity equations and PCL formula. The proposed solution method is a path-based partial linearization algorithm to approximately solve the restricted CDA-PCL-SUE. The proposed algorithm is a three-phase iterative process. Phase 1 is an entropy maximization problem on O-D flow space that can be solved by Bregman’s balancing algorithm. Phase 2 is a PCL SUE problem that can be solved by PCL formula. Phase 3 is line search. CDA-PCL-SUE is solved on a small network and a real network, the city of Winnipeg network. The proposed algorithms with the six line search methods, namely, golden section (GS), bisection (BS), Armijo’s rule (AR), method of successive averages (MSA), self-regulated averaging (SRA) scheme, and quadratic interpolation (QI) scheme, are compared in terms of various convergence characteristics: root mean square error, step size, KKT-based mean square error and objective function. In terms of computational efficiency, under different path set sizes, dispersion parameters, impedance parameters and demand levels, the following line search methods are ordered from best to worst: SRA, GS, AR, QI, BS and MSA. The performances of Armijo’s rule and QI have greater variances. The performance of QI is worse with the increase of the path set size. Given all other factors being the same, the increase of dispersion parameter, path set size or demand level yields the increase of CPU time, whereas the change of impedance parameter does not influence CPU time. In addition, CDA-PCL-SUE is compared with its multinomial-logit counterpart (CDA-MNL-SUE). Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Ampol Karoonsoontawong & Dung-Ying Lin, 2015. "Combined Gravity Model Trip Distribution and Paired Combinatorial Logit Stochastic User Equilibrium Problem," Networks and Spatial Economics, Springer, vol. 15(4), pages 1011-1048, December.
  • Handle: RePEc:kap:netspa:v:15:y:2015:i:4:p:1011-1048
    DOI: 10.1007/s11067-014-9279-x
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    References listed on IDEAS

    as
    1. Michael Florian & Sang Nguyen & Jacques Ferland, 1975. "On the Combined Distribution-Assignment of Traffic," Transportation Science, INFORMS, vol. 9(1), pages 43-53, February.
    2. Oppenheim, Norbert, 1993. "Equilibrium trip distribution/assignment with variable destination costs," Transportation Research Part B: Methodological, Elsevier, vol. 27(3), pages 207-217, June.
    3. Lam, William H. K. & Huang, Hai-Jun, 1992. "A combined trip distribution and assignment model for multiple user classes," Transportation Research Part B: Methodological, Elsevier, vol. 26(4), pages 275-287, August.
    4. Chen, Anthony & Pravinvongvuth, Surachet & Xu, Xiangdong & Ryu, Seungkyu & Chootinan, Piya, 2012. "Examining the scaling effect and overlapping problem in logit-based stochastic user equilibrium models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1343-1358.
    5. Yao, Jia & Chen, Anthony & Ryu, Seungkyu & Shi, Feng, 2014. "A general unconstrained optimization formulation for the combined distribution and assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 137-160.
    6. Patriksson, Michael, 1993. "A unified description of iterative algorithms for traffic equilibria," European Journal of Operational Research, Elsevier, vol. 71(2), pages 154-176, December.
    7. Henry Liu & Xiaozheng He & Bingsheng He, 2009. "Method of Successive Weighted Averages (MSWA) and Self-Regulated Averaging Schemes for Solving Stochastic User Equilibrium Problem," Networks and Spatial Economics, Springer, vol. 9(4), pages 485-503, December.
    8. Yang, Hai & Wong, S. C. & Wong, K. I., 2002. "Demand-supply equilibrium of taxi services in a network under competition and regulation," Transportation Research Part B: Methodological, Elsevier, vol. 36(9), pages 799-819, November.
    9. Boyce, D. E. & Janson, B. N., 1980. "A discrete transportation network design problem with combined trip distribution and assignment," Transportation Research Part B: Methodological, Elsevier, vol. 14(1-2), pages 147-154.
    10. Chen, Anthony & Kasikitwiwat, Panatda, 2011. "Modeling capacity flexibility of transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 105-117, February.
    11. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    12. Huang, Hai-Jun & Lam, William H. K., 1992. "Modified Evans' algorithms for solving the combined trip distribution and assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 26(4), pages 325-337, August.
    13. Dawei Li & Tomio Miwa & Takayuki Morikawa, 2014. "Considering En-Route Choices in Utility-Based Route Choice Modelling," Networks and Spatial Economics, Springer, vol. 14(3), pages 581-604, December.
    14. Bekhor, Shlomo & Prashker, Joseph N., 2008. "GEV-based destination choice models that account for unobserved similarities among alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 243-262, March.
    15. Damberg, Olof & Lundgren, Jan T. & Patriksson, Michael, 1996. "An algorithm for the stochastic user equilibrium problem," Transportation Research Part B: Methodological, Elsevier, vol. 30(2), pages 115-131, April.
    16. Yang, Hai & Bell, Michael G. H. & Meng, Qiang, 2000. "Modeling the capacity and level of service of urban transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(4), pages 255-275, May.
    17. Tam, M. L. & Lam, William H. K., 2000. "Maximum car ownership under constraints of road capacity and parking space," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(3), pages 145-170, April.
    18. Kitthamkesorn, Songyot & Chen, Anthony, 2014. "Unconstrained weibit stochastic user equilibrium model with extensions," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 1-21.
    19. Zhou, Zhong & Chen, Anthony & Wong, S.C., 2009. "Alternative formulations of a combined trip generation, trip distribution, modal split, and trip assignment model," European Journal of Operational Research, Elsevier, vol. 198(1), pages 129-138, October.
    20. Torbjörn Larsson & Michael Patriksson, 1992. "Simplicial Decomposition with Disaggregated Representation for the Traffic Assignment Problem," Transportation Science, INFORMS, vol. 26(1), pages 4-17, February.
    21. Maher, Mike, 1998. "Algorithms for logit-based stochastic user equilibrium assignment," Transportation Research Part B: Methodological, Elsevier, vol. 32(8), pages 539-549, November.
    22. Lamond, B. & Stewart, N. F., 1981. "Bregman's balancing method," Transportation Research Part B: Methodological, Elsevier, vol. 15(4), pages 239-248, August.
    23. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
    24. Xu, Meng & Chen, Anthony & Gao, Ziyou, 2008. "An improved origin-based algorithm for solving the combined distribution and assignment problem," European Journal of Operational Research, Elsevier, vol. 188(2), pages 354-369, July.
    25. Lam, William H. K. & Huang, Hai-Jun, 1992. "Calibration of the combined trip distribution and assignment model for multiple user classes," Transportation Research Part B: Methodological, Elsevier, vol. 26(4), pages 289-305, August.
    26. Erlander, S., 1990. "Efficient population behavior and the simultaneous choices of origins, destinations and routes," Transportation Research Part B: Methodological, Elsevier, vol. 24(5), pages 363-373, October.
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    3. Heng Zhang & Paat Rusmevichientong & Huseyin Topaloglu, 2020. "Assortment Optimization Under the Paired Combinatorial Logit Model," Operations Research, INFORMS, vol. 68(3), pages 741-761, May.

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