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