Title: The research of advances in adaptive genetic algorithm
Abstract: The traditional genetic algorithm works with a fixed probability of genetic operators. It brings inconvenience to the individual adaptive, where the population is easy to get evolved into a stagnant state, resulting in local convergence. In this paper, progressive optimization is introduced to perform 5 times of improvement on crossover operator and mutation operator. The other part of the research is focused on the solution to the maximum optimization of Shaffer's F6 test function by way of comparative experiments on improved genetic algorithms. Experimental results show that the improved genetic algorithms are effective.
Publication Year: 2011
Publication Date: 2011-09-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 6
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