IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v194y2009i2p432-451.html
   My bibliography  Save this article

Traffic assignment model with fuzzy level of travel demand: An efficient algorithm based on quasi-Logit formulas

Author

Listed:
  • Ghatee, Mehdi
  • Hashemi, S. Mehdi

Abstract

The place of fuzzy concepts in traffic assignment (TA) models has been studied in recent literature. Keeping fuzzy level of travel demand in mind, we propose a new TA model in which the travel costs of links are depended on their congestion. From the results of such fuzzy TA model, network planners are able to estimate the number of travelers on network links. By using zero-one variables, the proposed model is transformed into a crisp mixed-integer problem with respect to path-flow variables. In order to produce the Logit flows from this problem, Damberg et al. algorithm is modified. Then, the level of certainty is maximized and perceived travel delays are minimized. For a fixed certainty degree, the obtained solution, which is named the fuzzy equilibrium flow, satisfies a quasi-Logit formula similar to ordinary expression of the Logit route choice model. Eventually, we examine the quality of different path enumeration techniques in the proposed model.

Suggested Citation

  • Ghatee, Mehdi & Hashemi, S. Mehdi, 2009. "Traffic assignment model with fuzzy level of travel demand: An efficient algorithm based on quasi-Logit formulas," European Journal of Operational Research, Elsevier, vol. 194(2), pages 432-451, April.
    • Handle: RePEc:eee:ejores:v:194:y:2009:i:2:p:432-451
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(07)01219-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fisk, Caroline, 1980. "Some developments in equilibrium traffic assignment," Transportation Research Part B: Methodological, Elsevier, vol. 14(3), pages 243-255, September.
    2. Ouyang, Liang-Yuh & Chang, Hung-Chi, 2002. "A minimax distribution free procedure for mixed inventory models involving variable lead time with fuzzy lost sales," International Journal of Production Economics, Elsevier, vol. 76(1), pages 1-12, March.
    3. van der Zijpp, N.J. & Fiorenzo Catalano, S., 2005. "Path enumeration by finding the constrained K-shortest paths," Transportation Research Part B: Methodological, Elsevier, vol. 39(6), pages 545-563, July.
    4. 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.
    5. Ceylan, Halim & Bell, Michael G. H., 2004. "Traffic signal timing optimisation based on genetic algorithm approach, including drivers' routing," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 329-342, May.
    6. Lee, Huey-Ming & Yao, Jing-Shing, 1998. "Economic production quantity for fuzzy demand quantity, and fuzzy production quantity," European Journal of Operational Research, Elsevier, vol. 109(1), pages 203-211, August.
    7. Wen, Meilin & Iwamura, Kakuzo, 2008. "Fuzzy facility location-allocation problem under the Hurwicz criterion," European Journal of Operational Research, Elsevier, vol. 184(2), pages 627-635, January.
    8. Eugene L. Lawler, 1972. "A Procedure for Computing the K Best Solutions to Discrete Optimization Problems and Its Application to the Shortest Path Problem," Management Science, INFORMS, vol. 18(7), pages 401-405, March.
    9. Miller-Hooks, Elise & Mahmassani, Hani, 2003. "Path comparisons for a priori and time-adaptive decisions in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 146(1), pages 67-82, April.
    10. Villeneuve, Daniel & Desaulniers, Guy, 2005. "The shortest path problem with forbidden paths," European Journal of Operational Research, Elsevier, vol. 165(1), pages 97-107, August.
    11. Kikuchi, Shinya & Chakroborty, Partha, 2006. "Place of possibility theory in transportation analysis," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 595-615, September.
    12. Carlos F. Daganzo & Yosef Sheffi, 1977. "On Stochastic Models of Traffic Assignment," Transportation Science, INFORMS, vol. 11(3), pages 253-274, August.
    13. Clark, Stephen & Watling, David, 2005. "Modelling network travel time reliability under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 119-140, February.
    14. Watling, David, 2006. "User equilibrium traffic network assignment with stochastic travel times and late arrival penalty," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1539-1556, December.
    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. Dell'Olmo, Paolo & Gentili, Monica & Scozzari, Andrea, 2005. "On finding dissimilar Pareto-optimal paths," European Journal of Operational Research, Elsevier, vol. 162(1), pages 70-82, April.
    17. Henn, Vincent & Ottomanelli, Michele, 2006. "Handling uncertainty in route choice models: From probabilistic to possibilistic approaches," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1526-1538, December.
    18. Chen, Yuh-Wen & Tzeng, Gwo-Hshiung, 2001. "Using fuzzy integral for evaluating subjectively perceived travel costs in a traffic assignment model," European Journal of Operational Research, Elsevier, vol. 130(3), pages 653-664, May.
    19. Larsson, Torbjörn & Patriksson, Michael & Rydergren, Clas, 2004. "A column generation procedure for the side constrained traffic equilibrium problem," Transportation Research Part B: Methodological, Elsevier, vol. 38(1), pages 17-38, January.
    20. Akgun, Vedat & Erkut, Erhan & Batta, Rajan, 2000. "On finding dissimilar paths," European Journal of Operational Research, Elsevier, vol. 121(2), pages 232-246, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ji, Xiangfeng & Zhou, Xuemei & Ran, Bin, 2013. "A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1828-1839.
    2. Temelcan, Gizem & Kocken, Hale Gonce & Albayrak, Inci, 2021. "Fuzzy modelling of static system optimum traffic assignment problem having multi origin-destination pair," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    3. MacGregor Smith, J. & Cruz, F.R.B., 2014. "M/G/c/c state dependent travel time models and properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 560-579.
    4. Zhou, Bojian & Li, Xuhong & He, Jie, 2014. "Exploring trust region method for the solution of logit-based stochastic user equilibrium problem," European Journal of Operational Research, Elsevier, vol. 239(1), pages 46-57.
    5. Cruz, F.R.B. & van Woensel, T. & MacGregor Smith, J. & Lieckens, K., 2010. "On the system optimum of traffic assignment in M/G/c/c state-dependent queueing networks," European Journal of Operational Research, Elsevier, vol. 201(1), pages 183-193, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhaoqi Zang & Xiangdong Xu & Kai Qu & Ruiya Chen & Anthony Chen, 2022. "Travel time reliability in transportation networks: A review of methodological developments," Papers 2206.12696, arXiv.org, revised Jul 2022.
    2. Prakash, A. Arun & Seshadri, Ravi & Srinivasan, Karthik K., 2018. "A consistent reliability-based user-equilibrium problem with risk-averse users and endogenous travel time correlations: Formulation and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 171-198.
    3. Rasmussen, Thomas Kjær & Watling, David Paul & Prato, Carlo Giacomo & Nielsen, Otto Anker, 2015. "Stochastic user equilibrium with equilibrated choice sets: Part II – Solving the restricted SUE for the logit family," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 146-165.
    4. Ahipaşaoğlu, Selin Damla & Meskarian, Rudabeh & Magnanti, Thomas L. & Natarajan, Karthik, 2015. "Beyond normality: A cross moment-stochastic user equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 333-354.
    5. Du, Muqing & Tan, Heqing & Chen, Anthony, 2021. "A faster path-based algorithm with Barzilai-Borwein step size for solving stochastic traffic equilibrium models," European Journal of Operational Research, Elsevier, vol. 290(3), pages 982-999.
    6. Michael W. Levin & Melissa Duell & S. Travis Waller, 2020. "Arrival Time Reliability in Strategic User Equilibrium," Networks and Spatial Economics, Springer, vol. 20(3), pages 803-831, September.
    7. Amirgholy, Mahyar & Gonzales, Eric J., 2017. "Efficient frontier of route choice for modeling the equilibrium under travel time variability with heterogeneous traveler preferences," Economics of Transportation, Elsevier, vol. 11, pages 1-14.
    8. Xie, Chi & Liu, Zugang, 2014. "On the stochastic network equilibrium with heterogeneous choice inertia," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 90-109.
    9. Oyama, Yuki & Hara, Yusuke & Akamatsu, Takashi, 2022. "Markovian traffic equilibrium assignment based on network generalized extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 135-159.
    10. Patriksson, Michael, 2008. "On the applicability and solution of bilevel optimization models in transportation science: A study on the existence, stability and computation of optimal solutions to stochastic mathematical programs," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 843-860, December.
    11. Nie, Yu (Marco), 2011. "Multi-class percentile user equilibrium with flow-dependent stochasticity," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1641-1659.
    12. Guido Gentile, 2018. "New Formulations of the Stochastic User Equilibrium with Logit Route Choice as an Extension of the Deterministic Model," Service Science, INFORMS, vol. 52(6), pages 1531-1547, December.
    13. Bekhor, Shlomo & Toledo, Tomer, 2005. "Investigating path-based solution algorithms to the stochastic user equilibrium problem," Transportation Research Part B: Methodological, Elsevier, vol. 39(3), pages 279-295, March.
    14. Pushak, Yasha & Hare, Warren & Lucet, Yves, 2016. "Multiple-path selection for new highway alignments using discrete algorithms," European Journal of Operational Research, Elsevier, vol. 248(2), pages 415-427.
    15. Watling, David Paul & Rasmussen, Thomas Kjær & Prato, Carlo Giacomo & Nielsen, Otto Anker, 2015. "Stochastic user equilibrium with equilibrated choice sets: Part I – Model formulations under alternative distributions and restrictions," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 166-181.
    16. Uchida, Kenetsu, 2014. "Estimating the value of travel time and of travel time reliability in road networks," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 129-147.
    17. Chen, Anthony & Zhou, Zhong & Lam, William H.K., 2011. "Modeling stochastic perception error in the mean-excess traffic equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1619-1640.
    18. Nakayama, Shoichiro & Watling, David, 2014. "Consistent formulation of network equilibrium with stochastic flows," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 50-69.
    19. E. Nikolova & N. E. Stier-Moses, 2014. "A Mean-Risk Model for the Traffic Assignment Problem with Stochastic Travel Times," Operations Research, INFORMS, vol. 62(2), pages 366-382, April.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:194:y:2009:i:2:p:432-451. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.