Design a Fuzzy Goal Programming Model for Optimizing the Cost and Distance of Vehicles in the Four-Echelon Closed-Loop Supply Chain by Using Ant Colony Algorithm

In today's highly competitive world, closed-loop supply chains (CLSC) have become a major challenge for product recycling. The recycling system has a special place in the supply chain due to the coverage of laws and the reduction of environmental pollution, increasing economic power by creating new jobs and the ability to recover the value of returned products. The purpose of this study is to design fuzzy- goal model for optimizing the cost and distance of vehicles in the four echelon closed-loop supply chain. The closed-loop logistics model could not be easily solved with the base gradient methods due to its NP-Hard problem group, so the ant algorithm was used for optimization. Finally, after implementing the fuzzy goal model of the research, it was found that the goal of minimizing the cost in the model has a higher membership amount than the distance goal, and managers should pay special attention to this goal.