Optimization Multi-Objective Cost and Delay Rate in Delivering Orders in the Three- Echelon Reverse Supply Chain Based On Cost Management

Developing and establishing a logistics network is a strategic decision that its impacts last many years. Because of changes in customer’s demand over time a logistics network should be developed in an efficient manner that can respond to uncertainties. The objective of this research is to define the number of returned products to minimize total cost and delay time of reverse logistics. In this research, a fuzzy bi-objective optimization model was introduced in the reverse logistics system. The aim of this research is to determine the number of returned products that should be delivered to be recovered, processed and re manufactured in different time periods so that the total cost of reverse logistics and delay time to be minimized. To deal with ambiguity in the reverse logistics network, a fuzzy approach has been applied. To solve the problem in large scale, meta-heuristic algorithms of Cuckoo and Genetic were employed by applying MATLAB software. In order to compare two optimization algorithms, a series of sample problems have been generated then the results of the two algorithms were compared and superiority of each of them was discussed.