An integrated logistics model for emergency relief and rescue operation considering secondary disaster

Document Type : Research Paper

Authors

1 Department of Industrial Engineering, Tehran North Branch, Engineering Faculty, Islamic Azad University, Iran

2 Department of Industrial Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran

Abstract

In recent years, and after further studies on the effects of natural disasters and catastrophes that threaten human life, a new concept called secondary disasters has been proposed. The fact that all areas affected by natural disasters may be affected by secondary disasters is generally overlooked, and this has exacerbated the effects of disasters. Therefore, to reduce the human and economic effects of natural disasters, this article examines the issue of designing a supply chain for relief resources and providing optimal rescue operations, considering the possibility of primary and secondary disasters. Due to the dynamic nature of the secondary effects and the need for continuous updating of the relief management process, this paper presents a one-objective model of mixed nonlinear integer programming to meet the demand for relief items, rescue the injured and evacuate the affected peoples concerning the prioritization of demand points under the conditions of primary and secondary crises, minimizes transportation time, transportation costs and unsatisfied demand; also defines the priority of demand points based on the amount of unmet needs and duration of deprivation of relief items and services; in this view, demand points are prioritized and unmet needs is minimized. Since the problem of the current study falls into the category of Np-hard problems, in order to solve the model, a combined approach of genetic algorithm (GA) and rolling horizon planning is introduced, finally the proposed algorithm is based on a case study has been implemented on the existing data set, which shows the high quality of this solution method in terms of the quality of the solution and the computational time.

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  • Receive Date: 18 January 2022
  • Revise Date: 19 February 2022
  • Accept Date: 02 March 2022
  • First Publish Date: 02 March 2022