The Application Research Of Bionic Intelligent Algorithm In The Reverse Logistics Locatiom And Vehicle Routing Problem

In recent years, the rapid development of e-commerce, not only makes people shopping is more and more convenient, but also let people feel the advantages of information technology. But also because of the characteristics of e-commerce makes consumers in expectations of real objects and produce differences in the quality of the actual product is necessarily return the difference. This not only adds to the cost of electronic business enterprise, also is a wave of social resources. In this case, the design of reasonable distribution plan, energy efficiency, has great economic and social significance. However, the traditional solving algorithm can’t carry on the accurate, so many scholars began to use bionic intelligent algorithm to solve large-scale approximate optimal solution of the problem. So this paper introduces the various basic intelligent algorithm based on improved ant colony algorithm.The article is about the locations of the return of reverse logistics in e-commerce and the vehicle routing problem is studied, on the basis of considering vehicle routing for site selection.The first part is about the locations of the reverse logistics and vehicle routing problem of reviewed the related studies, analysis and study of the problems and the insufficiency, in the analysis are determined on the basis of the predecessors’ research in this paper, we study the main content;The second part is introduce the basic theory of reverse logistics and reverse logistics in the application of electronic commerce, including the reasons, effect, and the status quo and pattern;The third part is to construct the reverse logistics location path model, are considered in the model parameters with time Windows and deal with themulti-objective optimization function, makes the model more accurately reflect real life;In the fourth part is the vehicle routing problem solving algorithm research,mainly through introducing several heuristic algorithm for solving this kind of problem, through the simulation experiment to analyze the algorithm in solving the problem of the advantages and disadvantages;The fifth part mainly improved algorithm theory and experiment, this part is the focus of the article, mainly introduces improvement principle of algorithm, in this paper, from the smallest largest ant colony algorithm was improved, the maximum minimum ant colony algorithm to search the global solution is slow, introducing local algorithm 2- opt MMAS algorithm, at the same time to improve the algorithm in all aspects, including the selection strategy, the initial solution and pheromone update,etc., will these improvements validated by vehicle routing problem, solving the problem of VRP with time Windows. Matlab simulation experiment, the results of the comparison algorithm, and analyze the results;The sixth part is to summarize the main research content of this article, analysis and forecast the next research direction.The focus of this article is to improve the algorithm, in order to verify the validity of the algorithm, this paper apply them in real life, in case of data to verify the improved algorithm for reverse logistics location and the feasibility and effectiveness of vehicle routing problem solving.