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Genetic Algorithms (GA) is a method based on natural selection in the theory of biological evolution, which has been widely applied to solve numerous optimization problems in diverse fields. However, the canonical GA is more likely to get stuck at a local optimum and thereby leads to premature convergence. To overcome such inconvenience, a fuzzy adaptive GA (FAGA) is proposed based on fuzzy clustering...
To overcome global situation problem tradition genetic algorithm has very strong robustness in finding the solution, but crossover probability and mutation probability is fixed and invariable, it caused premature convergence and running inefficient to the solution on complicated problem at later evolution process of tradition genetic algorithm. To this problem the paper proposed a new algorithm with...
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