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Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers

Author

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  • Abbas Tarhini

    (Lebanese American University)

  • Kassem Danach

    (Islamic University of Lebanon)

  • Antoine Harfouche

    (Université Paris Nanterre)

Abstract

The vehicle routing problem (VRP) is a combinatorial optimization management problem that seeks the optimal set of routes traversed by a vehicle to deliver products to customers. A recognized problem in this domain is to serve ‘prioritized’ customers in the shortest possible time where customers with known demands are supplied by one or several depots. This problem is known as the Vehicle Routing with Prioritized Customers (VRPC). The purpose of this work is to present and compare two artificial intelligence-based novel methods that minimize the traveling distance of vehicles when moving cargo to prioritized customers. Various studies have been conducted regarding this topic; nevertheless, up to now, few studies used the Cuckoo Search-based hyper-heuristic. This paper modifies a classical mathematical model that represents the VRPC, implements and tests an evolutionary Cuckoo Search-based hyper-heuristic, and then compares the results with those of our proposed modified version of the Clarke Wright (CW) algorithm. In this modified version, the CW algorithm serves all customers per their preassigned priorities while covering the needed working hours. The results indicate that the solution selected by the Cuckoo Search-based hyper-heuristic outperformed the modified Clarke Wright algorithm while taking into consideration the customers’ priority and demands and the vehicle capacity.

Suggested Citation

  • Abbas Tarhini & Kassem Danach & Antoine Harfouche, 2022. "Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers," Annals of Operations Research, Springer, vol. 308(1), pages 549-570, January.
    • Handle: RePEc:spr:annopr:v:308:y:2022:i:1:d:10.1007_s10479-020-03625-5
    DOI: 10.1007/s10479-020-03625-5
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    References listed on IDEAS

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    1. Xianlong Ge & Ziqiang Zhu & Yuanzhi Jin, 2020. "Electric Vehicle Routing Problems with Stochastic Demands and Dynamic Remedial Measures," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-15, August.
    2. Zhen, Lu, 2016. "Modeling of yard congestion and optimization of yard template in container ports," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 83-104.
    3. Jean-François Côté & Michel Gendreau & Jean-Yves Potvin, 2020. "The Vehicle Routing Problem with Stochastic Two-Dimensional Items," Transportation Science, INFORMS, vol. 54(2), pages 453-469, March.
    4. Fink, Martin & Desaulniers, Guy & Frey, Markus & Kiermaier, Ferdinand & Kolisch, Rainer & Soumis, François, 2019. "Column generation for vehicle routing problems with multiple synchronization constraints," European Journal of Operational Research, Elsevier, vol. 272(2), pages 699-711.
    5. Edmund K Burke & Michel Gendreau & Matthew Hyde & Graham Kendall & Gabriela Ochoa & Ender Özcan & Rong Qu, 2013. "Hyper-heuristics: a survey of the state of the art," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(12), pages 1695-1724, December.
    6. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    7. Jin, Jianyong & Crainic, Teodor Gabriel & Løkketangen, Arne, 2012. "A parallel multi-neighborhood cooperative tabu search for capacitated vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 222(3), pages 441-451.
    8. Szeto, W.Y. & Wu, Yongzhong & Ho, Sin C., 2011. "An artificial bee colony algorithm for the capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 215(1), pages 126-135, November.
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    Cited by:

    1. Guy Assaker & Wassim Shahin, 2022. "What Drives Faculty Publication Citations in the Business Field? Empirical Results from an AACSB Middle Eastern Institution," Publications, MDPI, vol. 10(4), pages 1-29, November.

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