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首页> 外文期刊>IEEE Transactions on Neural Networks >Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space. Part II: Analysis of the diversification role of crossover
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Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space. Part II: Analysis of the diversification role of crossover

机译：连续空间中种群数量无限的演化算法的理论分析。第二部分：交叉的多元化作用分析

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For pt. I see ibid., p. 102-19. In this part of the paper the authors concentrate on the unique diversification role of the crossover operator in genetic algorithms. The explorative behavior of a generic crossover operator is revealed through a detailed large-sample analysis. Recursive equations for the population distributions are derived for a uniform crossover operator in multi-dimensional continuous space, showing how the crossover operator probes new regions of the solution space while keeping the population within the feasible region. The results of this analysis can be extended to the setting of a discrete space in a straightforward manner, shedding much light on the understanding of the essential role of crossover in genetic algorithms.
机译：对于pt。我见同上。 102-19。在本文的这一部分中，作者集中讨论了交叉算子在遗传算法中的独特多样化作用。通过详细的大样本分析可以揭示通用交叉算子的探索行为。推导了多维连续空间中统一交叉算子的总体分布递推方程，显示了交叉算子如何探查求解空间的新区域，同时将总体保持在可行区域内。该分析的结果可以直接扩展到离散空间的设置，从而大大减少了对遗传算法中交叉作用的理解。

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