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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/76705
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/76705

    Title: Solving p-Hub Median problems by genetic algorithr Taguchi method
    Authors: Tien, F.-C.;Lee, L.J.-H.;Yang, Su-Fen
    Contributors: 統計系
    Keywords: IIE Annual Conference and Exhibition 2004, 15 May 2004 through 19 May 2004, Houston, TX, 66321
    K-means algorithm;Objective cost function;Taguchi method;Genetic algorithms;Heuristic methods;Probability;Problem solving
    Date: 2004
    Issue Date: 2015-07-20 17:50:46 (UTC+8)
    Abstract: The p-Hub Median problem has been crucial problem that locates p hubs in a number of points, and allocates the remaining points to the hubs such that minimizes an objective cost function. Due to this problem is a NP-complete problem, heuristic methods have been popularly applied to this category of problems. In this paper, we propose a hybrid genetic algorithm that solves the p-Hub Median problem effectively. The proposed GA integrates different methods including multi-start, elite principle, critical event, K-means algorithm and different evolutionary operators to avoid local optimal solutions and increase the efficiency of genetic process. Because of using different methods, tuning up the hybrid GA becomes a critical task that derives a set of parameters leading the evolutionary process to a quick convergence. The parameters include the probabilities of crossover and mutation, the number of iterations for multi-start, the length of critical events, the number of iterations for running K-means algorithm. Therefore, the Taguchi method is used to find the best operating parameters based on several well-known test problems. Experiments show that the proposed hybrid genetic algorithm, tuned with the Taguchi method, effectively and efficiently solves the p-Hub Median problem.
    Relation: IIE Annual Conference and Exhibition 2004, 489
    Data Type: article
    Appears in Collections:[統計學系] 期刊論文

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