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

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 c...

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Bibliographic Details
Published in:Mathematical problems in engineering 2014-01, Vol.2014 (2014), p.1-7
Main Authors: Li, Ling, Liu, Jianyong, Zhu, Wanhong, Wang, Huaixiao, Yin, Zhuchen
Format: Article
Language:English
Subjects:
Algorithms
Classification
Clustering
Computational efficiency
Convergence
Defect annealing
Distribution centers
Distribution centres
Efficiency
Euclidean space
Evolutionary
Evolutionary algorithms
Genetic algorithms
Logistics
Mathematical problems
Optimization
Parameters
Searching
Simulated annealing
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Summary: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.
ISSN:1024-123X
1563-5147
DOI:10.1155/2014/714657