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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 714657, 7 pages
Research Article

Multidistribution Center Location Based on Real-Parameter Quantum Evolutionary Clustering Algorithm

College of Field Engineering, PLA University of Science and Technology, Nanjing 210007, China

Received 16 July 2014; Accepted 22 October 2014; Published 26 November 2014

Academic Editor: Xu Zhang

Copyright © 2014 Huaixiao Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


To determine the multidistribution center location and the distribution scope of the distribution center with high efficiency, the real-parameter quantum-inspired evolutionary clustering algorithm (RQECA) is proposed. RQECA is applied to choose multidistribution center location on the basis of the conventional fuzzy C-means clustering algorithm (FCM). The combination of the real-parameter quantum-inspired evolutionary algorithm (RQIEA) and FCM can overcome the local search defect of FCM and make the optimization result independent of the choice of initial values. The comparison of FCM, clustering based on simulated annealing genetic algorithm (CSAGA), and RQECA indicates that RQECA has the same good convergence as CSAGA, but the search efficiency of RQECA is better than that of CSAGA. Therefore, RQECA is more efficient to solve the multidistribution center location problem.