IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v60y2013i4p294-312.html
   My bibliography  Save this article

Generalized orienteering problem with resource dependent rewards

Author

Listed:
  • Jesse Pietz
  • Johannes O. Royset

Abstract

We introduce a generalized orienteering problem (OP) where, as usual, a vehicle is routed from a prescribed start node, through a directed network, to a prescribed destination node, collecting rewards at each node visited, to maximize the total reward along the path. In our generalization, transit on arcs in the network and reward collection at nodes both consume a variable amount of the same limited resource. We exploit this resource trade‐off through a specialized branch‐and‐bound algorithm that relies on partial path relaxation problems that often yield tight bounds and lead to substantial pruning in the enumeration tree. We present the smuggler search problem (SSP) as an important real‐world application of our generalized OP. Numerical results show that our algorithm applied to the SSP outperforms standard mixed‐integer nonlinear programming solvers for moderate to large problem instances. We demonstrate model enhancements that allow practitioners to represent realistic search planning scenarios by accounting for multiple heterogeneous searchers and complex smuggler motion. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013

Suggested Citation

  • Jesse Pietz & Johannes O. Royset, 2013. "Generalized orienteering problem with resource dependent rewards," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(4), pages 294-312, June.
  • Handle: RePEc:wly:navres:v:60:y:2013:i:4:p:294-312
    DOI: 10.1002/nav.21534
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.21534
    Download Restriction: no

    File URL: https://libkey.io/10.1002/nav.21534?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. James N. Eagle & James R. Yee, 1990. "An Optimal Branch-and-Bound Procedure for the Constrained Path, Moving Target Search Problem," Operations Research, INFORMS, vol. 38(1), pages 110-114, February.
    2. Hiroyuki Sato & Johannes O. Royset, 2010. "Path optimization for the resource‐constrained searcher," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(5), pages 422-440, August.
    3. Chao, I-Ming & Golden, Bruce L. & Wasil, Edward A., 1996. "A fast and effective heuristic for the orienteering problem," European Journal of Operational Research, Elsevier, vol. 88(3), pages 475-489, February.
    4. K. E. Trummel & J. R. Weisinger, 1986. "Technical Note—The Complexity of the Optimal Searcher Path Problem," Operations Research, INFORMS, vol. 34(2), pages 324-327, April.
    5. Johannes O. Royset & Hiroyuki Sato, 2010. "Route optimization for multiple searchers," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(8), pages 701-717, December.
    6. Jeffrey D. Camm & Amitabh S. Raturi & Shigeru Tsubakitani, 1990. "Cutting Big M Down to Size," Interfaces, INFORMS, vol. 20(5), pages 61-66, October.
    7. R. Ramesh & Yong-Seok Yoon & Mark H. Karwan, 1992. "An Optimal Algorithm for the Orienteering Tour Problem," INFORMS Journal on Computing, INFORMS, vol. 4(2), pages 155-165, May.
    8. Bruce L. Golden & Larry Levy & Rakesh Vohra, 1987. "The orienteering problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(3), pages 307-318, June.
    9. Jinxin Yi, 2003. "Vehicle Routing with Time Windows and Time-Dependent Rewards: A Problem from the American Red Cross," Manufacturing & Service Operations Management, INFORMS, vol. 5(1), pages 74-77.
    10. Robert F. Dell & James N. Eagle & Gustavo Henrique Alves Martins & Almir Garnier Santos, 1996. "Using multiple searchers in constrained‐path, moving‐target search problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(4), pages 463-480, June.
    11. Vansteenwegen, Pieter & Souffriau, Wouter & Oudheusden, Dirk Van, 2011. "The orienteering problem: A survey," European Journal of Operational Research, Elsevier, vol. 209(1), pages 1-10, 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. 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.
    2. Kim, Hyunjoon & Kim, Byung-In, 2022. "Hybrid dynamic programming with bounding algorithm for the multi-profit orienteering problem," European Journal of Operational Research, Elsevier, vol. 303(2), pages 550-566.
    3. Bijun Wang & Zheyong Bian & Mo Mansouri, 2023. "Self-adaptive heuristic algorithms for the dynamic and stochastic orienteering problem in autonomous transportation system," Journal of Heuristics, Springer, vol. 29(1), pages 77-137, February.
    4. Ksenia D Mukhina & Alexander A Visheratin & Denis Nasonov, 2019. "Orienteering Problem with Functional Profits for multi-source dynamic path construction," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-15, April.
    5. Qinxiao Yu & Yossiri Adulyasak & Louis-Martin Rousseau & Ning Zhu & Shoufeng Ma, 2022. "Team Orienteering with Time-Varying Profit," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 262-280, January.
    6. Yan Xia & Rajan Batta & Rakesh Nagi, 2017. "Controlling a Fleet of Unmanned Aerial Vehicles to Collect Uncertain Information in a Threat Environment," Operations Research, INFORMS, vol. 65(3), pages 674-692, June.

    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. 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.
    2. Kobeaga, Gorka & Rojas-Delgado, Jairo & Merino, María & Lozano, Jose A., 2024. "A revisited branch-and-cut algorithm for large-scale orienteering problems," European Journal of Operational Research, Elsevier, vol. 313(1), pages 44-68.
    3. H Tang & E Miller-Hooks, 2005. "Algorithms for a stochastic selective travelling salesperson problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(4), pages 439-452, April.
    4. Dominique Feillet & Pierre Dejax & Michel Gendreau, 2005. "Traveling Salesman Problems with Profits," Transportation Science, INFORMS, vol. 39(2), pages 188-205, May.
    5. Bourque, François-Alex, 2019. "Solving the moving target search problem using indistinguishable searchers," European Journal of Operational Research, Elsevier, vol. 275(1), pages 45-52.
    6. Angelelli, E. & Archetti, C. & Vindigni, M., 2014. "The Clustered Orienteering Problem," European Journal of Operational Research, Elsevier, vol. 238(2), pages 404-414.
    7. Kim, Hyunjoon & Kim, Byung-In, 2022. "Hybrid dynamic programming with bounding algorithm for the multi-profit orienteering problem," European Journal of Operational Research, Elsevier, vol. 303(2), pages 550-566.
    8. Steven M. Shechter & Farhad Ghassemi & Yasin Gocgun & Martin L. Puterman, 2015. "Technical Note—Trading Off Quick versus Slow Actions in Optimal Search," Operations Research, INFORMS, vol. 63(2), pages 353-362, April.
    9. Balcik, Burcu, 2017. "Site selection and vehicle routing for post-disaster rapid needs assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 30-58.
    10. Gambardella, L.M. & Montemanni, R. & Weyland, D., 2012. "Coupling ant colony systems with strong local searches," European Journal of Operational Research, Elsevier, vol. 220(3), pages 831-843.
    11. 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.
    12. Oleg Shcherbina & Elena Shembeleva, 2014. "Modeling recreational systems using optimization techniques and information technologies," Annals of Operations Research, Springer, vol. 221(1), pages 309-329, October.
    13. Vansteenwegen, Pieter & Souffriau, Wouter & Berghe, Greet Vanden & Oudheusden, Dirk Van, 2009. "A guided local search metaheuristic for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 196(1), pages 118-127, July.
    14. Rahma Lahyani & Mahdi Khemakhem & Frédéric Semet, 2017. "A unified matheuristic for solving multi-constrained traveling salesman problems with profits," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 393-422, September.
    15. Mei, Yi & Salim, Flora D. & Li, Xiaodong, 2016. "Efficient meta-heuristics for the Multi-Objective Time-Dependent Orienteering Problem," European Journal of Operational Research, Elsevier, vol. 254(2), pages 443-457.
    16. 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.
    17. Lin, Shih-Wei & Yu, Vincent F., 2012. "A simulated annealing heuristic for the team orienteering problem with time windows," European Journal of Operational Research, Elsevier, vol. 217(1), pages 94-107.
    18. Zheng, Weimin & Liao, Zhixue & Qin, Jing, 2017. "Using a four-step heuristic algorithm to design personalized day tour route within a tourist attraction," Tourism Management, Elsevier, vol. 62(C), pages 335-349.
    19. 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.
    20. Dang, Duc-Cuong & Guibadj, Rym Nesrine & Moukrim, Aziz, 2013. "An effective PSO-inspired algorithm for the team orienteering problem," European Journal of Operational Research, Elsevier, vol. 229(2), pages 332-344.

    More about this item

    Statistics

    Access and download statistics

    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:wly:navres:v:60:y:2013:i:4:p:294-312. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.