Research On Logistics Distribution Vehicle Routing Problem Based On Genetic Algorithm

Logistics has showed powerful function since it generated. As the groundwork of economic activity, logistics is known as the third profit source of enterprise. It can meet the requirements of modern business, and promote progress of the society and economy. So, it is important to promote the development and progress of logistics. Logistics has resulted in more and more attention.In the costs of logistics, transportation cost accounts for a very high percentage. Logistics distribution derived from the transportation in logistics system, it is an important link of logistics. The scheme of logistics distribution has great influence in logistics service, costs and benefit in delivery whether it is reasonable. Vehicle Routing Problem is the core of logistics distribution and one of the focus of research. Reasonable arrangement can facilitate the procedure of distribution, reduce the time of distribution, improve transport efficiency and reduce service costs effectively. So, it is necessary to do some research on Vehicle Routing Problem.Firstly, this paper introduced the status of the vehicle routing problem, described and analyzed the restriction condition of this problem, classified it based on different restriction condition and assignment requirement. Following those it summarized the existing algorithm for solving vehicle routing problem. Then, it introduced the basal conception, principle and manipulation of Simple Genetic Algorithm. After that it introduced its advantage and disadvantage and summarized the process of Simple Genetic Algorithm. And then it introduced the improved direction for Simple Genetic Algorithm.Secondly, this paper analyzed Capacitated Vehicle Routing Problem and established mathematics former. After that it introduced the method and process of Simple Genetic Algorithm which was used to solve Capacitated Vehicle Routing Problem. Then, it indicated the shortage of Simple Genetic Algorithm and put forward Improved Genetic Algorithm based on the coding project of second layer chromosome and adapted cross probability. Lastly, it validated the feasibility and validity of Improved Genetic Algorithm by test.