Abstract
Due to the increase in the number of natural disasters and the significant amounts of waste generated in these events, having a comprehensive framework for its management in the recovery and response phases of disaster is necessary. Hence, this research investigates the disaster waste management problem by simultaneous consideration of sustainability and resiliency. In this regard, a multi-objective mathematical model is presented to minimize total costs, environmental impacts, and transportation risks while maximizing social impacts and resilience of the logistics system. Since uncertainty is an integral part of disaster conditions, the research problem formulates the fuzzy robust stochastic optimization model under the hybrid uncertainty. Then, a real-world case study is studied in Golestan province, Iran. Afterward, transportation risks are calculated by adopting the fuzzy failure mode and effects analysis (FMEA) method, and then the proposed model is solved by a hybrid algorithm based on the multi-choice goal programming method and particle swarm optimization algorithm (PSO). Eventually, sensitivity analyses on some important model parameters are conducted, and practical managerial/theoretical implications are presented. The obtained results show the efficiency and performance of the model and the developed hybrid algorithm.
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