Logistics Distribution Vehicle Routing Algorithm Analysis And Research

As an advanced organization method and management technology, modern logistics has been recognized as "the third profit source" for an enterprise. It integrates the value chain of enterprises, reinforces the control capability and accelerates fund turnover by the reduction of circulation cost and time. So, it became more and more important for many companies in our country. For the bright future, both the government and company take the profit of the industry into consideration, and try to make it an important industry. By studying, the logistic ration is a big proportion in the cost constitution of the logistics. For the ration center, optimizing the route of ration can not only simplify the route, reduce the frequency of the delivery, but also low down the cost so as to create more benefit.The main idea of the thesis is studying how to optimize the route of ration. By analyzing the existing algorithms, it points out the problems to educe the main idea of thesis. First, we analyze VRP and introduce some algorithms to solve the problem. Based on studies on the existing algorithms, we choose the Genetic Algorithm to optimize the route of ration. After analyzing the principium and limitation of Simple Genetic Algorithm, we give two new feasible modes of optimizing the route of ration, Then based on the natural number coding theory, the Vehicle Routing Problem with Time Windows is studied. And by using a new Hybrid Genetic Algorithm solving an example of the VRPTW, we validate feasibility and good performance of this new algorithm. In the classical vehicle routing problems, all kinds of information are assumed to be determinated, but in practice, planner of routes always meet with uncertain information, such as fuzzy information. Consequently, effective methods for solving determinated vehicle routing problems cannot solve fuzzy vehicle routing problems effectively. It is necessary to do some research on characteristics of fuzzy vehicle routing problems and to design effective models and algorithms for it. So we give more efforts on studying the Fuzzy Vehicle Routing Problem. We introduce two methods to solve this problem and give a new design of genetic operation. In the last, we give a example of FVRP and provide a new design of result output.In conclusion, we point out main work of the dissertation and the orientation of future research prospective. Finally, I hope the work of this dissertation can provide a little profit to future practice.