A fuzzy multi-objective model for a sustainable end of life vehicle reverse logistic network design: two meta-heuristic algorithms

In recent years, the concept of reverse logistics has been paid attention by many researchers due to the importance of environmental regulations as well as the importance of utilising from worn-out goods for re-production. The purpose of the present study was to develop a mixed fuzzy integer linear planning model for reverse logistics network of end of life (EOL) vehicles to minimise the cost of establishing and constructing facilities, as well as minimising transportation and material costs between facilities, minimising environmental impacts, and maximising social responsibility with taking into account the uncertainty conditions and the multi-product mode. Due to the NP-HARD nature of the understudied problem, the whale optimisation algorithm (WOA) and NSGA-II algorithm were used to solve the model, which results of these two modes were comprised based on quality indicators, dispersion and uniformity and solution time of the problem.