Faculty of Industrial & Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
Nowadays supply chain management (SCM) is an interesting problem that has attracted the attention of many researchers. Transportation network design is one of the most important fields of SCM. In this paper, an integrated multi-stage and multi-product logistic network design including forward and reverse logistic is considered. At first, a mixed integer nonlinear programming model (MINLP) is formulated in such a way as to minimize purchasing and transportation costs. Then, a hybrid priority-based genetic algorithm (pb-GA) and simulated annealing algorithm (SA) is developed in two phases to find the proper solutions. The solution is represented by a matrix and a vector. Response surface methodology (RSM) is used in order to tune the significant parameters of the algorithm. Several test problems are generated in order to examine the proposed meta-heuristic algorithm performance.