Research On Optimization Model Of Commercial Returns Reverse Logistics Networks

As forward logistics, reverse logistics is also a component of supply chain. But reverse logistics has distinguished difference with forward logistics, mainly on origination point and cost. It is complicated to study the cost of reverse logistics, whose controllability is weak. Commercial returns is an inevitable process in logistics, it mainly springs from retail trade and customer. The colony reverse logistics faced with is numerous, and complicated as well. The paper conducts a rather detailed research aiming at how to minimize the cost of commercial returns.The paper introduces the concept and driving factors of reverse logistics, and compares it with forward logistics to find the similarities and differences between them. Besides that, it also introduces the characteristics, types and building environment of the reverse logistics networks.Commercial returns system can be expressed by a network which is composed by three kinds of coupling points including customers, initial point and reclaiming center and the transportation route between them. The paper established a mathematical model, and its goal is to minimize the overall cost including initial point related cost, reclaiming center related cost and transportation cost while insuring customers'convenience to return products. The model is a nonlinear mixed integer programming model, because the amount of decision variables is big and the relation between them is complicated, the paper solves the model with double layer GA on basis of general GA.To validate of the model, the paper applies the model to a case, by programming with Visual C++, it provides the case a concrete solution according to the result of program running. At the same time, it conducts a sensitivity analysis to the main parameters of GA and model to post their influence to the best solution.