RESEARCH ON VRP OF OPTIMIZING BASED ON FUZZY C-MEANS CLUSTERING AND IGA UNDER ELECTRONIC COMMERCE
The logistic distribution under electronic commerce has the characteristic of dispersive customer positions, large order forms, little batches and many repeated routes. The traditional optimizing vehicle routing problems meet with diversified problems in different extents and are difficult to play their roles. Therefore, according to the particularity of logistic distribution under electronic commerce, the improved two-phase algorithm needs to be adopted to get solutions.Namely, the customer group can be divided into several regions using fuzzy c-means clustering algorithm in first phase.And it is decomposed into some small-scale subsets according with restraint conditions with scan algorithm in each region.In second phase, get the solutions of the customer point in every group using the improved genetic algorithm. In fact it is route optimization problems of several single TSP model. In the end, the test proves the validity of this improved algorithm combining with examples.
Electronic commerce logistic system optimization vehicle routing problem fuzzy c-means clustering improved genetic algorithm improved two-phase algorithm
CHUN-YU REN XIAO-BO WANG JIN-YING SUN
School of Information Science and Technology, Heilongjiang University, Harbin 150080, P.R.China School of Management, Harbin Institute of Technology, Harbin, 150001, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
2461-2467
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）