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Location-allocation problem for resource distribution under uncertainty in disaster relief operations

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  • Shaw, Lipika
  • Das, Soumen Kumar
  • Roy, Sankar Kumar

Abstract

Disaster disrupts society to lead a normal life by causing huge casualties and damages or loss of properties, environment, or essential services of a society or a nation. In the case of a catastrophe, a suitable resource management program is needed to distribute resources efficiently among the people of the areas affected by the calamity. In this work, we propose a mixed-integer non-linear mathematical model related to resource management. We consider a multi-objective optimization problem to provide the maximum services to the people by determining the positions of the distribution centers. This humanitarian logistic model optimizes three criteria: (i) minimizing the cost, (ii) minimizing the time, (iii) maximizing the affected coverage area. Due to the impreciseness of the disastrous environment, some parameters of the model are chosen as a triangular type-2 fuzzy number in order to deal with the uncertainty. An improved neutrosophic compromise programming is incorporated to solve the stated problem. Therefore the solutions are compared with the other two existing techniques, such as the novel method and fuzzy TOPSIS. Three numerical examples are considered to explain the model properly. After that, a sensitivity analysis is performed to visualize the impact of demand, supply and capacity on the objective functions. Finally, conclusions and future scopes related to this study are drawn.

Suggested Citation

  • Shaw, Lipika & Das, Soumen Kumar & Roy, Sankar Kumar, 2022. "Location-allocation problem for resource distribution under uncertainty in disaster relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    • Handle: RePEc:eee:soceps:v:82:y:2022:i:pa:s0038012122000106
    DOI: 10.1016/j.seps.2022.101232
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    2. Akbari, Leilanaz & Kazemi, Ahmad & Salari, Majid, 2023. "Operational planning of vehicles for rescue and relief operations considering the unavailability of the relocated vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).

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