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An analysis of generalised heuristics for vehicle routing and personnel rostering problems

Author

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  • Mustafa Misir

    (KU Leuven, Department of Computer Science, CODeS & iMinds-ITEC, Gent, Belgium)

  • Pieter Smet

    (KU Leuven, Department of Computer Science, CODeS & iMinds-ITEC, Gent, Belgium)

  • Greet Vanden Berghe

    (KU Leuven, Department of Computer Science, CODeS & iMinds-ITEC, Gent, Belgium)

Abstract

The present study investigates the performance of heuristics while solving problems with routing and rostering characteristics. The target problems include scheduling and routing home care, security and maintenance personnel. In analysing the behaviour of the heuristics and determining the requirements for solving the aforementioned problems, the winning hyper-heuristic from the first International Cross-domain Heuristic Search Challenge (CHeSC 2011) is employed. The completely new application of a hyper-heuristic as an analysis tool offers promising perspectives for supporting dedicated heuristic development. The experimental results reveal that different low-level heuristics perform better on different problems and that their performance varies during a search process. The following characteristics affect the performance of the heuristics: the planning horizon, the number of activities and lastly the number of resources. The body of this paper details both these characteristics and also discusses the required features for embedding in an algorithm to solve problems particularly with a vehicle routing component.

Suggested Citation

  • Mustafa Misir & Pieter Smet & Greet Vanden Berghe, 2015. "An analysis of generalised heuristics for vehicle routing and personnel rostering problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(5), pages 858-870, May.
    • Handle: RePEc:pal:jorsoc:v:66:y:2015:i:5:p:858-870
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    Cited by:

    1. Muhammed Abdullah Gencer & Hacı Mehmet Alakas & Mehmet Pinarbasi & Tamer Eren, 2024. "Railway security personnel scheduling problem considering personnel preferences," Journal of Transportation Security, Springer, vol. 17(1), pages 1-21, December.
    2. Laura Malagodi & Ettore Lanzarone & Andrea Matta, 2021. "Home care vehicle routing problem with chargeable overtime and strict and soft preference matching," Health Care Management Science, Springer, vol. 24(1), pages 140-159, March.
    3. Ehsan Pourjavad & Eman Almehdawe, 2022. "Optimization of the technician routing and scheduling problem for a telecommunication industry," Annals of Operations Research, Springer, vol. 315(1), pages 371-395, August.
    4. Li, Yanfeng & Xiang, Ting & Szeto, Wai Yuen, 2021. "Home health care routing and scheduling problem with the consideration of outpatient services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    5. Yadav, Niteesh & Tanksale, Ajinkya, 2022. "An integrated routing and scheduling problem for home healthcare delivery with limited person-to-person contact," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1100-1125.
    6. Paraskevopoulos, Dimitris C. & Laporte, Gilbert & Repoussis, Panagiotis P. & Tarantilis, Christos D., 2017. "Resource constrained routing and scheduling: Review and research prospects," European Journal of Operational Research, Elsevier, vol. 263(3), pages 737-754.
    7. Emir Hüseyin Özder & Evrencan Özcan & Tamer Eren, 2019. "Staff Task-Based Shift Scheduling Solution with an ANP and Goal Programming Method in a Natural Gas Combined Cycle Power Plant," Mathematics, MDPI, vol. 7(2), pages 1-26, February.
    8. Pouria Khodabandeh & Vahid Kayvanfar & Majid Rafiee & Frank Werner, 2021. "A Bi-Objective Home Health Care Routing and Scheduling Model with Considering Nurse Downgrading Costs," IJERPH, MDPI, vol. 18(3), pages 1-24, January.
    9. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    10. Drake, John H. & Kheiri, Ahmed & Özcan, Ender & Burke, Edmund K., 2020. "Recent advances in selection hyper-heuristics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 405-428.

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