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Solving the humanitarian multi-trip cumulative capacitated routing problem via a grouping metaheuristic algorithm

Author

Listed:
  • Maliheh Khorsi

    (Tarbiat Modares University)

  • Seyed Kamal Chaharsooghi

    (Tarbiat Modares University)

  • Ali Husseinzadeh Kashan

    (Tarbiat Modares University)

  • Ali Bozorgi-Amiri

    (University of Tehran)

Abstract

Every year, natural disasters such as earthquakes, floods, volcanos, etc. cause millions of victims. So a quick response to these disasters is vital to reduce their negative consequences. Vehicle routing models can make important contributions to faster response, and thus, save lives. This paper proposes a vehicle routing problem to deliver relief resources from origins to destinations in response to disasters. For this purpose, a multi-period, multi-depot, multi-trip mixed-integer linear programming model is developed. Minimizing the sum of arrival times is considered as a service-based objective function for the increase of the survival rate. For the first time, the problem is solved using a grouping metaheuristic algorithm. Then its performance is compared with two other grouping algorithms. To evaluate the solution method, the algorithms are implemented on various test problems and compared statistically. Additionally, to show the validity of the model, sensitivity analyses are performed and managerial insights are given.

Suggested Citation

  • Maliheh Khorsi & Seyed Kamal Chaharsooghi & Ali Husseinzadeh Kashan & Ali Bozorgi-Amiri, 2022. "Solving the humanitarian multi-trip cumulative capacitated routing problem via a grouping metaheuristic algorithm," Annals of Operations Research, Springer, vol. 319(1), pages 173-210, December.
    • Handle: RePEc:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-022-04757-6
    DOI: 10.1007/s10479-022-04757-6
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    References listed on IDEAS

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