Regional Logistics System Bi-level Programming with Elastic Demand by Using Fuzzy C-means Clustering

The bi-level programming of regional logistics system in elastic demand was studied by using fuzzy c-means clustering. Game relations among the government, the owners of the logistics centers, and the clients were discussed by system analysis method. The synthetic evaluation indices of 17 characteristic vectors were established. The problem is equal to that of determining the membership values to the given logistics centers or the clustering centers by using the thought of fuzzy c-means clustering. The clustering centers are some of the feasible sites that possess candidacy of the logistics centers. Stackelberg model was established. The upper level model is the problem for the government to seek maximal social benefits with elastic demand. The lower level model is the partition problem of clients’ assignment. Genetic algorithm was adopted in the concrete course for solution. The simulation result shows its correctness.

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