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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/28484


    標題: A High-Performance Genetic Algorithm: Using Traveling Salesman Problem as a Case
    作者: Tsai, Chun-Wei
    Tseng, Shih-Pang
    Chiang, Ming-Chao
    Yang, Chu-Sing
    Hong, Tzung-Pei
    貢獻者: 資訊多媒體應用系
    關鍵字: COMBINATORIAL OPTIMIZATION
    EVOLUTION
    MODEL
    日期: 2014
    上傳時間: 2015-05-06 21:17:58 (UTC+8)
    出版者: Hindawi Publishing Corporation
    摘要: This paper presents a simple but efficient algorithm for reducing the computation time of genetic algorithm (GA) and its variants. The proposed algorithm is motivated by the observation that genes common to all the individuals of a GA have a high probability of surviving the evolution and ending up being part of the final solution; as such, they can be saved away to eliminate the redundant computations at the later generations of a GA. To evaluate the performance of the proposed algorithm, we use it not only to solve the traveling salesman problem but also to provide an extensive analysis on the impact it may have on the quality of the end result. Our experimental results indicate that the proposed algorithm can significantly reduce the computation time of GA and GA-based algorithms while limiting the degradation of the quality of the end result to a very small percentage compared to traditional GA.
    關聯: Scientific World Journal, 178621
    Appears in Collections:[資訊多媒體應用系] 期刊論文

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