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  • 标题:Revision of a Floating-Point Genetic Algorithm GENOCOP V for Nonlinear Programming Problems
  • 本地全文:下载
  • 作者:K. Kato ; M. Sakawa ; H. Katagiri
  • 期刊名称:The Open Cybernetics & Systemics Journal
  • 电子版ISSN:1874-110X
  • 出版年度:2008
  • 卷号:2
  • 期号:1
  • 页码:24-29
  • DOI:10.2174/1874110X00802010024
  • 出版社:Bentham Science Publishers Ltd
  • 摘要:

    In this paper, focusing on general nonlinear programming problems, we attempt to propose a general and highperformance approximate solution method for them. In recent years, S. Koziel et al. have proposed a floating-point genetic algorithm, GENOCOP V, as a general approximate solution method for nonlinear programming problems and showed its efficiency, there are left some shortcomings of the method. In this paper, incorporating ideas to cope with these shortcomings, we propose a revised GENOCOP V (RGENOCOP V). Furthermore, we show the efficiency of the proposed method RGENOCOP V by comparing it with two existing methods, RGENOCOP III and GENOCOP V through the application of them into the numerical examples.

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