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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/21081

    题名: Dynamic programming decision path encoding of genetic algorithms for production allocation problems
    作者: Chang, Ying-Hua;Hou, Young-Chang
    贡献者: 淡江大學資訊管理學系
    关键词: Genetic Algorithms;Dynamic programming decision path encoding;Production allocation;Constraints satisfaction;Optimization problems
    日期: 2008-02-01
    上传时间: 2009-11-30 13:13:12 (UTC+8)
    出版者: Kidlington: Pergamon
    摘要: Genetic algorithm is a novel optimization technique for solving constrained optimization problems. The penalty function methods are the popular approaches because of their simplicity and ease of implementation. Penalty encoding method needs more generations to get good solutions because it causes invalid chromosomes during evolution. In order to advance the performance of Genetic Algorithms for solving production allocation problems, this paper proposes a new encoding method, which applies the upper/lower bound concept of dynamic programming decision path on the chromosome encoding of genetic algorithm, that encodes constraints into chromosome to ensure that chromosomes are all valid during the process of evolution. Utilization of the implicated parallel processing characteristic of genetic algorithms to improve dynamic programming cannot guarantee to solve complex problems in the polynomial time. Additionally, a new simultaneous crossover and mutation operation is proposed to enable the new method to run correctly following the standard genetic algorithm procedures. This approach is evaluated on some test problems. Solutions obtained by this approach indicate that our new encoding genetic algorithms certainly accelerate the performance of the evolution process.
    關聯: Computers & Industrial Engineering 54(1), pp.53-65
    DOI: 10.1016/j.cie.2007.06.034
    显示于类别:[資訊管理學系暨研究所] 期刊論文


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