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Diversity and Multimodal Search with a Hybrid Two-Population GA: An Application to ANN Development

机译:杂交双人GA的多样性和多模式搜索:ANN发展的应用

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Being based on the theory of evolution and natural selection, the Genetic Algorithms (GA) represent a technique that has been proved as good enough for the resolution of those problems that require a search through a complex space of possible solutions. The maintenance of a population of possible solutions that are in constant evolution may lead to its diversity being lost, consequently it would be more difficult, not only the achievement of a final solution but also the supply of more than one solution The method that is described here tries to overcome those difficulties by means of a modification in traditional GA's. Such modification involves the inclusion of an additional population that might avoid the mentioned loss of diversity of classical GA's. This new population would also provide the piece of exhaustive search that allows to provide more than one solution.
机译:基于进化和自然选择的理论,遗传算法(GA)代表了一种技术,该技术已被证明足以解决需要通过可能解决方案的复杂空间搜索的那些问题的解决问题。维持持续进化的可能解决方案的群体可能导致其多样性丢失,因此它将更加困难,而不仅可以实现最终解决方案,而且还更加困难,而且更加困难,还可以更加困难,而且更加困难,还可以更加困难,而且更加困难,还可以更加困难,而且还更加困难,而且还更加困难,还可以更加困难,而且还更加困难,而且还更加困难,还可以更加困难,而且还更加困难,而且还更加困难,而且更加困难。在这里试图通过传统GA的修改来克服这些困难。这种修改涉及包含额外的人群,可能避免提到的古典GA的多样性损失。这一新人口还将提供允许提供多个解决方案的详尽搜索。

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