Diagonal crossover in genetic algorithms for numerical optimization

A.E.Eiben; Cees H.M.Van Kemenade

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Diagonal crossover in genetic algorithms for numerical optimization

机译：遗传算法中的对角交叉用于数值优化

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In this paper the results of a detailed investigation on a multi-parent recombination operator, diagonal crossover, are reported. Although earlier publications have indicted the high per- formance of diagonal crossover on a number of problems, so far it has not been investigated whether high performance is indeed a re- sult of using a high number of parents. Here we formulate three hypotheses to explain why GA performance increases when more parents are used. Based on an extensive study on a test suite con- taining eight numerical optimization problems we are able to estab- lish that the higher number of parents is indeed one of the sources of higher performance, if and when this occurs.

机译：在本文中，报告了对多亲子重组算子对角交叉的详细研究结果。尽管较早的出版物指出了许多问题上对角交叉的高性能，但到目前为止，尚未研究高性能是否确实是使用大量父母的结果。在这里，我们提出了三个假设，以解释为什么当使用更多的父母时GA绩效会提高。基于对包含八个数值优化问题的测试套件的广泛研究，我们能够确定，如果发生这种情况，更高数量的父母确实是更高性能的来源之一。

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来源
《Control and Cybernetics》 |1997年第3期|p.447-465|共19页
作者
A.E.Eiben; Cees H.M.Van Kemenade;
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正文语种 eng
中图分类控制论、信息论（数学理论）;自动化技术、计算机技术;
关键词
genetic algorithms; numerical optimization; recombination;

机译：遗传算法;数值优化;重组;

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Diagonal crossover in genetic algorithms for numerical optimization

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