IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v44y1998i11-part-2ps125-s136.html
   My bibliography  Save this article

Stochastic Shortest Path Problems with Piecewise-Linear Concave Utility Functions

Author

Listed:
  • Ishwar Murthy

    (Department of Information Systems and Decision Sciences, Louisiana State University, Baton Rouge, Lousiana 70803)

  • Sumit Sarkar

    (School of Management, University of Texas at Dallas, Richardson, Texas 75080)

Abstract

This paper considers a stochastic shortest path problem where the arc lengths are independent random variables following a normal distribution. In this problem, the optimal path is one that maximizes the expected utility, with the utility function being piecewise-linear and concave. Such a utility function can be used to approximate nonlinear utility functions that capture risk averse behaviour for a wide class of problems. The principal contribution of this paper is the development of exact algorithms to solve large problem instances. Two algorithms are developed and incorporated in labelling procedures. Computational testing is done to evaluate the performance of the algorithms. Overall, both algorithms are very effective in solving large problems quickly. The relative performance of the two algorithms is found to depend on the "curvature" of the piecewise linear utility function.

Suggested Citation

  • Ishwar Murthy & Sumit Sarkar, 1998. "Stochastic Shortest Path Problems with Piecewise-Linear Concave Utility Functions," Management Science, INFORMS, vol. 44(11-Part-2), pages 125-136, November.
    • Handle: RePEc:inm:ormnsc:v:44:y:1998:i:11-part-2:p:s125-s136
    DOI: 10.1287/mnsc.44.11.S125
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.44.11.S125
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.44.11.S125?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Nejat Karabakal & Jack R. Lohmann & James C. Bean, 1994. "Parallel Replacement under Capital Rationing Constraints," Management Science, INFORMS, vol. 40(3), pages 305-319, March.
    2. Desrochers, Martin & Soumis, Francois, 1988. "A reoptimization algorithm for the shortest path problem with time windows," European Journal of Operational Research, Elsevier, vol. 35(2), pages 242-254, May.
    3. Ishwar Murthy & Sumit Sarkar, 1996. "A Relaxation-Based Pruning Technique for a Class of Stochastic Shortest Path Problems," Transportation Science, INFORMS, vol. 30(3), pages 220-236, August.
    4. Jonathan F. Bard & James E. Bennett, 1991. "Arc Reduction and Path Preference in Stochastic Acyclic Networks," Management Science, INFORMS, vol. 37(2), pages 198-215, February.
    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. Francis Sourd & Olivier Spanjaard, 2008. "A Multiobjective Branch-and-Bound Framework: Application to the Biobjective Spanning Tree Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 472-484, August.
    2. Yueyue Fan & Yu Nie, 2006. "Optimal Routing for Maximizing the Travel Time Reliability," Networks and Spatial Economics, Springer, vol. 6(3), pages 333-344, September.
    3. 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.
    4. Wang, Li & Yang, Lixing & Gao, Ziyou, 2016. "The constrained shortest path problem with stochastic correlated link travel times," European Journal of Operational Research, Elsevier, vol. 255(1), pages 43-57.
    5. Sam Ransbotham & Ishwar Murthy & Sabyasachi Mitra & Sridhar Narasimhan, 2011. "Sequential Grid Computing: Models and Computational Experiments," INFORMS Journal on Computing, INFORMS, vol. 23(2), pages 174-188, May.
    6. Axel Parmentier, 2019. "Algorithms for non-linear and stochastic resource constrained shortest path," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(2), pages 281-317, April.
    7. Alejandro Toriello & William B. Haskell & Michael Poremba, 2014. "A Dynamic Traveling Salesman Problem with Stochastic Arc Costs," Operations Research, INFORMS, vol. 62(5), pages 1107-1125, October.
    8. Manseur, Farida & Farhi, Nadir & Nguyen Van Phu, Cyril & Haj-Salem, Habib & Lebacque, Jean-Patrick, 2020. "Robust routing, its price, and the tradeoff between routing robustness and travel time reliability in road networks," European Journal of Operational Research, Elsevier, vol. 285(1), pages 159-171.
    9. Huang, He & Gao, Song, 2012. "Optimal paths in dynamic networks with dependent random link travel times," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 579-598.
    10. Chunling Luo & Chin Hon Tan, 2020. "Almost Stochastic Dominance for Most Risk-Averse Decision Makers," Decision Analysis, INFORMS, vol. 17(2), pages 169-184, June.
    11. Qi, Jin & Sim, Melvyn & Sun, Defeng & Yuan, Xiaoming, 2016. "Preferences for travel time under risk and ambiguity: Implications in path selection and network equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 264-284.
    12. Nie, Yu (Marco) & Wu, Xing & Dillenburg, John F. & Nelson, Peter C., 2012. "Reliable route guidance: A case study from Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 403-419.
    13. Jian Li & Amol Deshpande, 2019. "Maximizing Expected Utility for Stochastic Combinatorial Optimization Problems," Mathematics of Operations Research, INFORMS, vol. 44(1), pages 354-375, 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. Murthy, Ishwar & Sarkar, Sumit, 1997. "Exact algorithms for the stochastic shortest path problem with a decreasing deadline utility function," European Journal of Operational Research, Elsevier, vol. 103(1), pages 209-229, November.
    2. Nie, Yu (Marco) & Wu, Xing & Dillenburg, John F. & Nelson, Peter C., 2012. "Reliable route guidance: A case study from Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 403-419.
    3. Axel Parmentier, 2019. "Algorithms for non-linear and stochastic resource constrained shortest path," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(2), pages 281-317, April.
    4. Elisabeth Lübbecke & Marco E. Lübbecke & Rolf H. Möhring, 2019. "Ship Traffic Optimization for the Kiel Canal," Operations Research, INFORMS, vol. 67(3), pages 791-812, May.
    5. Peiling Wu & Joseph C. Hartman & George R. Wilson, 2005. "An Integrated Model and Solution Approach for Fleet Sizing with Heterogeneous Assets," Transportation Science, INFORMS, vol. 39(1), pages 87-103, February.
    6. Yang, Baiyu & Miller-Hooks, Elise, 2004. "Adaptive routing considering delays due to signal operations," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 385-413, June.
    7. Belanger, Nicolas & Desaulniers, Guy & Soumis, Francois & Desrosiers, Jacques, 2006. "Periodic airline fleet assignment with time windows, spacing constraints, and time dependent revenues," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1754-1766, December.
    8. Formaneck, Steven D. & Cozzarin, Brian P., 2013. "Technology adoption and training practices as a constrained shortest path problem," Omega, Elsevier, vol. 41(2), pages 459-472.
    9. Hernandez, Florent & Feillet, Dominique & Giroudeau, Rodolphe & Naud, Olivier, 2016. "Branch-and-price algorithms for the solution of the multi-trip vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 249(2), pages 551-559.
    10. Michael Zabarankin & Stan Uryasev & Robert Murphey, 2006. "Aircraft routing under the risk of detection," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 728-747, December.
    11. Timo Gschwind & Stefan Irnich, 2012. "Effective Handling of Dynamic Time Windows and Synchronization with Precedences for Exact Vehicle Routing," Working Papers 1211, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    12. Tang, Jiafu & Yu, Yang & Li, Jia, 2015. "An exact algorithm for the multi-trip vehicle routing and scheduling problem of pickup and delivery of customers to the airport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 73(C), pages 114-132.
    13. Suzanne Childress & Pablo Durango‐Cohen, 2005. "On parallel machine replacement problems with general replacement cost functions and stochastic deterioration," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 409-419, August.
    14. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    15. Keng Hoo Chuah & Jon C. Yingling, 2005. "Routing for a Just-in-Time Supply Pickup and Delivery System," Transportation Science, INFORMS, vol. 39(3), pages 328-339, August.
    16. Michelle Dunbar & Gary Froyland & Cheng-Lung Wu, 2012. "Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework," Transportation Science, INFORMS, vol. 46(2), pages 204-216, May.
    17. Dayarian, Iman & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2015. "A column generation approach for a multi-attribute vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 241(3), pages 888-906.
    18. Silke Jütte & Marc Albers & Ulrich W. Thonemann & Knut Haase, 2011. "Optimizing Railway Crew Scheduling at DB Schenker," Interfaces, INFORMS, vol. 41(2), pages 109-122, April.
    19. Sarac, Abdulkadir & Batta, Rajan & Rump, Christopher M., 2006. "A branch-and-price approach for operational aircraft maintenance routing," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1850-1869, December.
    20. Range, Troels Martin, 2013. "Exploiting Set-Based Structures to Accelerate Dynamic Programming Algorithms for the Elementary Shortest Path Problem with Resource Constraints," Discussion Papers on Economics 17/2013, University of Southern Denmark, Department of Economics.

    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:inm:ormnsc:v:44:y:1998:i:11-part-2:p:s125-s136. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.