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Please use this identifier to cite or link to this item: https://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 楊素芬
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:	[Department of Statistics] Periodical Articles

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