The Optimization Research Of H Corporation VRPB Based On Improved Genetic Algorithm Method

With the continuous development of the society and the demand of the enterpriseon saving logistics cost is more and more intense，the reverse logistics begins tobecome the important component of the enterprise logistics gradually and is being paidattention by the enterprise more and more. As the same as forward logistics, distributionis also one of the core part of the reverse logistics. The research on vehicle routingproblem of the reverse logistics is an important way to optimize the reverse logisticsdistribution. As the extension of vehicle routing problem, vehicle routing problem withbackhauls considers the goods delivery process of the vehicle and the goods pick-upprocess of the vehicle by integration. Through the research of vehicle routing problem,on one hand，it achieves the full saving and use of the vehicle resource, reduces the costof the distribution, improves the system of the transportation and the distribution. Onthe other hand, it embodies integrity and comprehensiveness of the research on therouting problem. It enriches the theory system of vehicle routing problem. Above all, ithas a strong significance of theory and reality.The paper firstly describes domestic and foreign status of vehicle routing problemand vehicle routing problem with backhauls and combines the relevant knowledge ofreverse logistics and vehicle routing problem, and then it comes up with vehicle routingproblem with backhauls and analyzes its character. Secondly, the paper explains thestatus of H corporation logistics dispatching and points out the existing problem in theprocess of dispatching. The paper analyzes the situation of vehicle routing problem withbackhauls of the corporation and points out the relevant factors that influences theproblem based on the operation flow of the corporation reverse logistics. Thirdly, thepaper designs the optimization scheme on the existing problem of vehicle routingproblem with backhauls of the corporation. It includes the improved strategydesignation of canceling limitation of the pick-ups and the deliveries, the arrangementof vehicle routing and the construction of mathematics. Finally, the paper uses theimproved genetic algorithm to solve the problem model. Through the solution, itembodies the optimization effect of the problem.