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A heuristic-based multi-choice goal programming for the stochastic sustainable-resilient routing-allocation problem in relief logistics

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Abstract

Natural or man-made disasters impose destructive effects like human injuries and urban infrastructure damages, which lead to disruptions that affect the entire distribution system. This research addresses the routing-allocation problem in the response phase of disaster management. The related literature shows that the researchers had less attention to some features like sustainability and resiliency in the mentioned problem. Hence, to cover these gaps, this study proposes a scenario-based multi-objective programming model to examine the resilient-sustainable routing-allocation problem considering the concept of fairness. The proposed model aims at minimizing total traveling time, total environmental impacts and total demand loss. The fuzzy robust stochastic optimization approach is utilized to cope with uncertain data arisen in disaster conditions. Then, due to the complexity of the research problem, a hybrid approach based on the multi-choice goal programming method and a heuristic algorithm is developed to solve the problem in a reasonable time. A case study is then selected to demonstrate the efficiency of the proposed model and the developed method. Finally, sensitivity analyses have been conducted in some parameters of the model and also the robustness of the solution has been investigated.

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Authors and Affiliations

  1. Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran

    Zakie Mamashli

  2. School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Ali Bozorgi-Amiri, Iman Dadashpour, Sina Nayeri & Jafar Heydari

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  1. Zakie Mamashli
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  2. Ali Bozorgi-Amiri
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  3. Iman Dadashpour
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  4. Sina Nayeri
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  5. Jafar Heydari
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Correspondence to Ali Bozorgi-Amiri.

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Appendix 1: Table related to the amounts of fuzzy scenario demands

Appendix 1: Table related to the amounts of fuzzy scenario demands

See Table 11.

Table 11 The amounts of fuzzy scenario demands of each crisis point
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Mamashli, Z., Bozorgi-Amiri, A., Dadashpour, I. et al. A heuristic-based multi-choice goal programming for the stochastic sustainable-resilient routing-allocation problem in relief logistics. Neural Comput & Applic 33, 14283–14309 (2021). https://doi.org/10.1007/s00521-021-06074-8

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