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Genetic Algorithms (GAs) and Their Mathematical Foundations
Abstract
In this chapter, the authors back GA procedures using old mathematical facts. More rigorous working of mathematical facts about GAs are raised in this chapter. In fact, there are a large number of similarities in the population of strings. The authors see how GA exploits these similarities to generate good solutions. So, in this whole procedure they show which schema or pattern will grow and which pattern will die or be lost as generation passes by due to the effect of selection, crossover, and mutation operator. The study of this building block hypothesis, leads to better understanding of GA. It will also help us to reach optimal solutions in much less time.
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