Mathematical Modeling of Tire’s Multi-Objective Supply Chain Network at Uncertainty circumstances and solving it using Meta-Heuristic algorithms

Supply chain network design is one of the most important issues in supply chain management. Therefore, the purpose of this study is to design a closed loop supply chain network in conditions of uncertainty and solve it using meta-heuristic algorithms.

This research is of applied kind. In this research, field and library study methods were used to collect information. Considering the selection of the tire industry as the under study industry for designing the proposed supply chain network, in this study, using field research, the required data from Kian Tire, Iran Tire, Dena Tire, Barez Tire, Kavir Tire, Yazd Tire, Artaville Tire and Pars Tire were collected and used to solve the model.

The modeling of this chain is done based on environmental considerations, minimizing the total cost of the chain and maximizing the response to customer demand. Finally, this model is solved using NRGA and NSGAII meta-heuristic algorithms and the obtained results are compared with each other. Also for credit evaluation suggested model using limitation epsilon method has been implemented in the GAMS software too.

In this research, the design of closed-loop supply chain network in conditions of uncertainty and its solution using meta-heuristic algorithms is considered and based on the research results, executive proposals were presented.