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A Practical Schema Theorem for Genetic Algorithm Design and Tuning

机译:遗传算法设计和优化的实用模式定理

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摘要

This paper develops the theory that can enable the design of genetic algorithms and choose the parameters such that the proportion of the best building blocks grow. A practical schema theorem has been used for this purpose and its ramification for the choice of selection operator and parameterization of the algorithm is explored. In particular stochastic universal selection, tournament selection, and truncation selection schemes are employed to verify the results. Results agree with the schema theorem and indicate that it must be obeyed in order to ascertain sustained growth of good building blocks. The analysis suggests that schema theorem alone is insufficient to guarantee the success of a selectorecombinative genetic algorithm.
机译:本文提出了一种理论,该理论可以设计遗传算法并选择参数,以使最佳构建基块的比例增加。一个实用的模式定理已用于此目的,并探讨了选择算子的选择和算法参数化的后果。特别地,采用随机通用选择,锦标赛选择和截断选择方案来验证结果。结果与图式定理一致,并表明必须遵循该定理才能确定良好构件的持续增长。分析表明,仅方案定理不足以保证选择组合遗传算法的成功。

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