Optimization Research Of Vehicle Distribution Routing Based On Genetic Algorithm For HY Bottled Water Company

With the development of the society and the continuous improvement of people’sliving standard, people pay more and more attention to the quality of drinking water.Therefore, healthy bottled water is changing quietly in our daily life instead of tap water, atthe same time, the distribution problem of the bottled water is also widely concerned.Because the distribution cost accounting for a large proportion of the company cost and italso being a way of serving customers, the fast and timely delivery is very important inorder to improve its efficiency and competitiveness. HY Bottled Water Company has itsown independent distribution subsidiary, undertaking the task of distribution of bottledwater. As its distribution routing of this company is assigned by the staffs’ experience forthese years, which have not already adapted to the trend of modern distribution, using thescientific way of distribution is of great importance. This paper analyzes the practicaldistribution problems for solving the distribution problem of HY Bottled Water Companybased on the mathematical model, the improved genetic algorithm and the simulationsoftware of Matlab.The detailed research contents are as follows:Firstly, this paper simply introduces the related theory of the distribution, the concept,elements, classification of distribution and the principles and methods of distributionrouting, as well as several kinds of mathematical model of vehicle routing and thealgorithm of solving model.Secondly, this paper analyzes the present situation of its distribution and finds out theproblems, to build a mathematical model based on the company’s total cost at least and theconstraint of meeting customers’ requirements, and the improved genetic algorithm.Finally, using the simulation software Matlab respectively solves the problem ofvehicle distribution routing based on the improved genetic algorithm and traditionalgenetic algorithm. Compared with the simulation results and the original path, it shows thatusing the improved genetic algorithm can reduce the total cost, shorten the transportationdistance, and improve the benefit of the company.