Study Of Optimizing Logistics Distribution Routing Problem Based On Clustering-Genetic Algorithm

With the continuous economic and social development, logistics need more scientific and reasonable, globalization, information technology, networking and intelligent, in order to create greater profits for the enterprise, it has become "the third profit source." The distribution of logistics activities which is directly connected to the final consumer is in the "final configuration". All the costs in the logistics activities, distribution costs account for a very high proportion. How to create more effective, reasonable, appropriate and accurate logistics which can better distribution arrangements for the path influences the costs, efficiency, effectiveness, speed of the distribution. Applying scientific, rational and efficient approach to optimize the logistics distribution routing problem is of great importance in a modern logistics and distribution activities.What's more, how to decide distribution routing problem in Logistics and distribution activities plays an important role in recent study of distribution routing problem research and applications. However, because of its computational complexity, almost the entire logistics distribution routing problem belongs to NP problems, efficient and accurate algorithm is unlikely to exist. Moreover, this paper will combine cluster analysis and genetic algorithm and apply to vehicle routing problem in logistics distribution. Accordingly, based on clustering and Genetic Algorithm, we will propose clustering-Genetic Algorithm to solve the problem of optimization of distribution routing problem.With the maturing of heuristic algorithms, many experts and scholars has proposed the improved heuristic algorithm to solve practical problems of vehicle routing problem. In order to overcome the Shortcomings of traditional binary encoding rules, this article alter the coding rules of genetic algorithm, that is, natural number coding rules. In addition, the paper has designed a randomized switch to control the mutation operation of genetic algorithm for the sake of avoiding the occurrence of local optimization. With regard to the clustering analysis technology, we have classified the customer of the distribution center by the integrated priority clustering. Finally, by bettering the distribution route optimization model, this paper has proposed the mathematical model based on clustering-Genetic Algorithm to optimize the vehicle routing problem. Because of the limitation of time, what I have studied has many deficiencies. In a word, more research work should be put on in near future.Figure 8 Table 7 References 75...