A Study On Logistics Network Optimization Model For 3PLs

In today's fiercely competing market environment, a growing number of companies have begun to realize the importance of logistics management. And logistics outsourcing (including both forward and reverse logistics outsourcing) has become a important means to enhance company's competitive power. It is a great chance for the development of Third Party Logistics services provider (3PLs), whose business focus on logistics outsourcing. In order to improve the costumer services and cut down the total logistics cost, 3PLs must improve their logistics networks to support both forward and reverse logistics management. Therefore, this paper analyzed the forward and reverse logistics network optimization problem for 3PLs respectively. Then, based on the former analyses, we proposed a mixed integer nonlinear programming model (ILM) to optimize the integrated forward/reverse logistics network for 3PLs. It is a NP hard problem. Usually, the traditional Genetic Algorithm (GA) is used to solve such problems. But GA has a high probability to appear premature when confronted with complex problems. Thus, we propose a hybrid Immune Algorithm (IA) based heuristic containing a simplex algorithm as a sub-search process. The numerical results obtained from the proposed method are compared with the outcomes gained by a common hybrid GA. The result of the comparison clearly indicates that the performance of the proposed IA is much better than the common GA.