TY - JOUR ID - 142824 TI - Introducing a fuzzy robust integrated model for optimizing humanitarian supply chain processes JO - Journal of Applied Research on Industrial Engineering JA - JARIE LA - en SN - 2538-5100 AU - Donyavi Rad, Meysam AU - Sadeh, Ehsan AU - Amini Sabegh, Zeinolabedin AU - Ehtesham Rasi, Reza AD - Department of Management, College of Human Science, Saveh Branch, Islamic Azad University, Saveh, Iran. AD - Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran. Y1 - 2023 PY - 2023 VL - 10 IS - 3 SP - 427 EP - 453 KW - Critical Logistics KW - Primary and Secondary Crises KW - Fuzzy Robust Integrated Programming KW - meta-heuristic algorithm DO - 10.22105/jarie.2022.284946.1323 N2 - The natural disasters of the last few decades clearly reveal that natural disasters impose high financial and human costs on governments and communities. Concerns in this regard are growing day by day. Making the right decisions and taking appropriate and timely measures in each phase of the crisis management cycle will reduce potential damage at the time of the disaster and reduce the vulnerability of society. Therefore, in this research, a mathematical model of crisis logistics planning considering the problem of primary and secondary crisis in disaster relief is introduced, which is the innovation of this research. In the primary crisis, the goal is to provide services and relief goods to crisis areas, and in the second stage, the secondary crisis that occurs after the primary crisis seeks to provide relief to crisis centers and transfer the injured to relief centers.  Therefore, this research proposes a mathematical fuzzy ideal programming model in two primary and secondary crises. In the primary crisis, the goal is to provide services and relief goods to crisis-stricken areas. The secondary crisis, which occurs after the primary crisis, aims to support crisis-stricken centers and move injured people to relief bases in the second step. According to the proposed model, Bertsimas-Sim’s fuzzy programming that formulation proposed by Bertsimas and Sim [1] and robust approach we initially used. The Epsilon constraint method was used to solve the low-dimensional model. Multi-objective meta-heuristic algorithms have been designed to handle the computational complexity of large-scale real-time problems. Multiple comparisons and analyses have been proposed to assess the performance of the model and problem-solving capabilities. The results indicate that the proposed approach can be applied and implemented to develop a real-world humanitarian logistics network. UR - https://www.journal-aprie.com/article_142824.html L1 - https://www.journal-aprie.com/article_142824_031a3125a7d21d5fa4530f9af97e4896.pdf ER -