Study On The Vehicle Routing Problems With Backhauls Of Reverse Logistics

With the rapid development of the world economy and modern technology, logistics industry is growing quickly all over the world. The reverse logistics which has been ignored by academia and business circle for a long time is gradually being paid attention to because of the implementing gradually thoroughly of sustainable development strategy. In our country the researches of the reverse logistics, particular in the Vehicle Routing Problems with Backhauls (VRPB) is at the threshold compared with foreign research results.VRPB is the extension of the Vehicle Routing Problems (VRP) which serves only either linehaul customers or backhaul customers. VRPB can serve both linehaul customers and backhaul customers by a fleet of vehicles so that it can reduce the cost of the transportation. How to arrange proper route to cut the cost of logistics operations is a key problem that every logistics manager has to face.Firstly, the paper introduces the definition of the reverse logistics, points the characteristic of the VRP in the reverse logistics through the comparison of the VRP in the logistics and the reverse logistics. On the basis of this, points that the VRPB which is used in this paper doesn't have the restriction that all backhauls have to be visited after all linehauls as the VRPB which all linehauls and backhauls aren't mixed. Then the VRPB mathematical model and special constraints are analyzed. The VRPB is solved by the improve Genetic Algorithms (GA) which is chose by the comparison of the different algorithms. Finally, illustration is given through a case study.The paper adds a restriction of time windows on the VRPB on the basis of the reality of logistics industry, and then the Vehicle Routing Problems with Backhauls and Time Windows (VRPBTW) mathematical model and special constraints are analyzed and solved by the Max-Min Ant Colony Algorithms (MMACA). Finally, the results which are solved by the MMACA are better than the traditional algorithms on the example. Therefore, the MMACA can reduce the cost of the transportation in reality so as to realize the optimization of the VRPBTW.