Designing a New Multi-objective Model for a Forward/Reverse Logistic Network Considering Customer Responsiveness and Quality Level

In today’s competitive world, the need to supply chain management (SCM) is more than ever. Since the purpose of logistic problems is minimizing the costs of organization to create favorable time and place for the products, SCM seek to create competitive advantage for their organizations and increase their productivity. This paper proposes a new multi-objective model for integrated forward / reverse logistics network including three objective functions which belongs to the class of NP-hard problems. The first objective attempts to minimize the total cost of the supply chain network. The second objective attempts to maximize the customer service level (customer responsiveness) in both forward and reverse networks. The third objective tries to minimize the total number of defects of in raw material obtained from suppliers and thus increase the quality level. To solve the proposed model, the non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranked genetic algorithms (NRGA) are used. A Taguchi experimental design method was applied to set and estimate the proper values of GAs parameters for improving their performances. Besides, to evaluate the performance of the two algorithms some numerical examples are produced and analyzed with some metrics to determine which algorithm works better. In order to determine whether there is a significant difference between the performances of the algorithms, the one-way A‌N‌O‌V‌A and Tukey test are used at 0.95 confidence level. Finally, the performance of the algorithms is analyzed and the results are reported.