Document Type : SI:RSSCMMA

Authors

1 Department of Industrial Engineering, Faculty of Mechanic and Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 P.hd in Entrepreneursship, Faculty member in Guilan ACECR, Educational member in Guilan UAST

3 School of industrial engineering, College of engineering, University of Tehran, Tehran, Iran

4 Department of industrial management, Islamic Azad University, Science and Research branch

5 Lecturer, department of computer science, Farhangian university, Tehran, Iran

10.22105/jarie.2021.299798.1365

Abstract

During natural and abnormal accidents, many people are injured, and a large number of wastes and rubbish are produced, so it is necessary to collect the injured and take them to treatment centers, which must be done in the reaction phase. Also, in the recovery and reconstruction phase, since a large amount of hazardous and non-hazardous waste is produced during accidents, effective measures should be taken to collect and recycle them if necessary. Both of these cases can be considered as a reverse logistics problem. This paper investigates reverse logistics planning in the response, improvement, and reconstruction phases in earthquake conditions. Due to the nature of the problem, it is expected that we will face a multi-objective problem, and the problem condition causes the issue of uncertainty. By increasing the dimensions of the problem, the NSGA-II meta-heuristic algorithm has been used to solve the two-objective model of the problem and the result indicates that the proposed solution algorithm works well and the quality of the answer and its solution time are appropriate. The results indicate that as capacity increases, the number of distribution centers built to meet demand decreases and the distribution center constructed may be far from some shelters, leading to increased transportation costs. According to the mentioned issues, this research uses reverse logistics in the response and recovery phases. Also, information about Tehran city will be used as data for the case study.

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