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The orienteering problem with stochastic travel and service times

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  • Ann Campbell
  • Michel Gendreau
  • Barrett Thomas

Abstract

In this paper, we introduce a variant of the orienteering problem in which travel and service times are stochastic. If a delivery commitment is made to a customer and is completed by the end of the day, a reward is received, but if a commitment is made and not completed, a penalty is incurred. This problem reflects the challenges of a company who, on a given day, may have more customers than it can serve. In this paper, we discuss special cases of the problem that we can solve exactly and heuristics for general problem instances. We present computational results for a variety of parameter settings and discuss characteristics of the solution structure. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • Ann Campbell & Michel Gendreau & Barrett Thomas, 2011. "The orienteering problem with stochastic travel and service times," Annals of Operations Research, Springer, vol. 186(1), pages 61-81, June.
    • Handle: RePEc:spr:annopr:v:186:y:2011:i:1:p:61-81:10.1007/s10479-011-0895-2
    DOI: 10.1007/s10479-011-0895-2
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    Cited by:

    1. Bock, Stefan, 2020. "Optimally solving a versatile Traveling Salesman Problem on tree networks with soft due dates and multiple congestion scenarios," European Journal of Operational Research, Elsevier, vol. 283(3), pages 863-882.
    2. Verbeeck, C. & Vansteenwegen, P. & Aghezzaf, E.-H., 2016. "Solving the stochastic time-dependent orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 255(3), pages 699-718.
    3. Wolfgang Wörndl & Alexander Hefele & Daniel Herzog, 2017. "Recommending a sequence of interesting places for tourist trips," Information Technology & Tourism, Springer, vol. 17(1), pages 31-54, March.
    4. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2020. "Multi-period orienteering with uncertain adoption likelihood and waiting at customers," European Journal of Operational Research, Elsevier, vol. 282(1), pages 288-303.
    5. Qinxiao Yu & Chun Cheng & Ning Zhu, 2022. "Robust Team Orienteering Problem with Decreasing Profits," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3215-3233, November.
    6. Timothy M. Sweda & Irina S. Dolinskaya & Diego Klabjan, 2017. "Adaptive Routing and Recharging Policies for Electric Vehicles," Transportation Science, INFORMS, vol. 51(4), pages 1326-1348, November.
    7. Wu, Qinghua & He, Mu & Hao, Jin-Kao & Lu, Yongliang, 2024. "An effective hybrid evolutionary algorithm for the clustered orienteering problem," European Journal of Operational Research, Elsevier, vol. 313(2), pages 418-434.
    8. Wolfgang Wörndl & Alexander Hefele & Daniel Herzog, 0. "Recommending a sequence of interesting places for tourist trips," Information Technology & Tourism, Springer, vol. 0, pages 1-24.
    9. Krzysztof Ostrowski & Joanna Karbowska-Chilinska & Jolanta Koszelew & Pawel Zabielski, 2017. "Evolution-inspired local improvement algorithm solving orienteering problem," Annals of Operations Research, Springer, vol. 253(1), pages 519-543, June.
    10. Yu, Qinxiao & Fang, Kan & Zhu, Ning & Ma, Shoufeng, 2019. "A matheuristic approach to the orienteering problem with service time dependent profits," European Journal of Operational Research, Elsevier, vol. 273(2), pages 488-503.
    11. Anupam Gupta & Ravishankar Krishnaswamy & Viswanath Nagarajan & R. Ravi, 2015. "Running Errands in Time: Approximation Algorithms for Stochastic Orienteering," Mathematics of Operations Research, INFORMS, vol. 40(1), pages 56-79, February.
    12. Evers, L. & Glorie, K.M. & van der Ster, S. & Barros, A.I. & Monsuur, H., 2012. "The Orienteering Problem under Uncertainty Stochastic Programming and Robust Optimization compared," Econometric Institute Research Papers EI 2012-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    14. Lei, Chao & Lin, Wei-Hua & Miao, Lixin, 2014. "A multicut L-shaped based algorithm to solve a stochastic programming model for the mobile facility routing and scheduling problem," European Journal of Operational Research, Elsevier, vol. 238(3), pages 699-710.
    15. Gunawan, Aldy & Lau, Hoong Chuin & Vansteenwegen, Pieter, 2016. "Orienteering Problem: A survey of recent variants, solution approaches and applications," European Journal of Operational Research, Elsevier, vol. 255(2), pages 315-332.
    16. Bian, Zheyong & Liu, Xiang, 2018. "A real-time adjustment strategy for the operational level stochastic orienteering problem: A simulation-aided optimization approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 246-266.
    17. John S. F. Lyons & Peter C. Bell & Mehmet A. Begen, 2018. "Solving the Whistler-Blackcomb Mega Day Challenge," Interfaces, INFORMS, vol. 48(4), pages 323-339, August.
    18. Shu Zhang & Jeffrey W. Ohlmann & Barrett W. Thomas, 2018. "Dynamic Orienteering on a Network of Queues," Transportation Science, INFORMS, vol. 52(3), pages 691-706, June.
    19. Zhang, Shu & Ohlmann, Jeffrey W. & Thomas, Barrett W., 2014. "A priori orienteering with time windows and stochastic wait times at customers," European Journal of Operational Research, Elsevier, vol. 239(1), pages 70-79.
    20. Dolinskaya, Irina & Shi, Zhenyu (Edwin) & Smilowitz, Karen, 2018. "Adaptive orienteering problem with stochastic travel times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 1-19.
    21. Samita Kedkaew & Warisa Nakkiew & Parida Jewpanya & Wasawat Nakkiew, 2024. "A Novel Tourist Trip Design Problem with Stochastic Travel Times and Partial Charging for Battery Electric Vehicles," Mathematics, MDPI, vol. 12(18), pages 1-19, September.

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