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Joint chance constrained shortest path problem with Copula theory

Author

Listed:
  • Zohreh Hosseini Nodeh

    (University of Tabriz)

  • Ali Babapour Azar

    (University of Tabriz)

  • Rashed Khanjani Shiraz

    (University of Tabriz)

  • Salman Khodayifar

    (Institute for Advanced Studies in Basic Sciences (IASBS))

  • Panos M. Pardalos

    (University of Florida)

Abstract

In this paper, we investigate the constrained shortest path problem where the arc resources of the problem are dependent normally distributed random variables. A model is presented to maximize the probability of all constraints, while not exceeding a certain amount. We assume that the rows of the constraint matrix are dependent, so we use a marginal distribution of the Copula functions, instead of the distribution functions and the dependency is driven by an appropriate Archimedean Copula. Then, we transform the joint chance-constrained problems into deterministic problems of second-order cone programming. This is a new approach where considers the dependency between resource consumptions and connects Copulas to stochastic resource constrained shortest path problem (SRCSPP). The results indicate that the effect of marginal probability levels is considerable. Moreover, the linear relaxation of SRCSPP is generally not convex; thus we can use lower and upper bounds of the second-order cone programming approximation to solve the relaxation problem. The experimental results show that the SRCSPP with Copula theory can achieve efficient performance.

Suggested Citation

  • Zohreh Hosseini Nodeh & Ali Babapour Azar & Rashed Khanjani Shiraz & Salman Khodayifar & Panos M. Pardalos, 2020. "Joint chance constrained shortest path problem with Copula theory," Journal of Combinatorial Optimization, Springer, vol. 40(1), pages 110-140, July.
    • Handle: RePEc:spr:jcomop:v:40:y:2020:i:1:d:10.1007_s10878-020-00562-8
    DOI: 10.1007/s10878-020-00562-8
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    References listed on IDEAS

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    1. Li Guan & Jianping Li & Weidong Li & Junran Lichen, 2019. "Improved approximation algorithms for the combination problem of parallel machine scheduling and path," Journal of Combinatorial Optimization, Springer, vol. 38(3), pages 689-697, October.
    2. George B. Dantzig, 2010. "Linear Programming Under Uncertainty," International Series in Operations Research & Management Science, in: Gerd Infanger (ed.), Stochastic Programming, chapter 0, pages 1-11, Springer.
    3. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    4. Gerard Cornuejols & Marshall L. Fisher & George L. Nemhauser, 1977. "Exceptional Paper--Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms," Management Science, INFORMS, vol. 23(8), pages 789-810, April.
    5. CORNUEJOLS, Gérard & FISHER, Marshall L. & NEMHAUSER, George L., 1977. "Location of bank accounts to optimize float: An analytic study of exact and approximate algorithms," LIDAM Reprints CORE 292, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Zhang, Yuli & Max Shen, Zuo-Jun & Song, Shiji, 2017. "Lagrangian relaxation for the reliable shortest path problem with correlated link travel times," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 501-521.
    7. Chunlin Xin & Letu Qingge & Jiamin Wang & Binhai Zhu, 2015. "Robust optimization for the hazardous materials transportation network design problem," Journal of Combinatorial Optimization, Springer, vol. 30(2), pages 320-334, August.
    8. Nie, Yu (Marco) & Wu, Xing, 2009. "Shortest path problem considering on-time arrival probability," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 597-613, July.
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    Cited by:

    1. Rashed Khanjani-Shiraz & Ali Babapour-Azar & Zohreh Hosseini-Noudeh & Panos M. Pardalos, 2022. "Distributionally robust maximum probability shortest path problem," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 140-167, January.
    2. Hosseini-Nodeh, Zohreh & Khanjani-Shiraz, Rashed & Pardalos, Panos M., 2023. "Portfolio optimization using robust mean absolute deviation model: Wasserstein metric approach," Finance Research Letters, Elsevier, vol. 54(C).

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