REINFORCED GA ALGORITHM WITH ADAPTIVE FUZZY GRADING MEASUREMENT APPLICATION TO TSP PROBLEM; 適應性模糊測度強化之基因演算法應用於解 TSP 問題

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题名:	REINFORCED GA ALGORITHM WITH ADAPTIVE FUZZY GRADING MEASUREMENT APPLICATION TO TSP PROBLEM;適應性模糊測度強化之基因演算法應用於解 TSP 問題
作者:	Huang, Chih-Peng;黃志鵬
贡献者:	臺北市立大學資訊科學系
关键词:	Genetic Algorithm (GA);Fuzzy Clustering;Travel Salesman Problem (TSP)
日期:	2013-07
上传时间:	2019-02-14
摘要:	This work mainly investigates the genetic algorithm (GA) associated with the notation of fuzzy theory and applications. The proposed crossover model for GA algorithm is guided via the grade of fuzzy membership functions, and the applicability is demonstrated by solving the travel salesman problem (TSP). The crossover model for the traditional GA use the probability rule to produce the next generation, where it always cause the time consumption for the useless evaluation. Thus, we study a distinct crossover model for GA algorithm associate with the fuzzy grade notion; this dynamic guide mode for GA algorithm can speed up the convergent process and improve the efficiency and the error rate from the simulating results. The experiments are performed and verified by the international benchmarks with TSPLIB and compared with some other ones.
關聯:	Business and Information 2013，Bali, Indonesia，2013/07/07~09
显示于类别:	[Department of Computer Science] Proceedings

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