Performance Evaluation of Genetic Algorithm in Noisy Environments

"The average of best" and "the standard deviation of best" were proposed to evaluate the performance of genetic algorithms in noisy environment.Results show the evaluation indexes could effectively evaluate the performance of genetic algorithm in the environment.Based on this,the performances of real-coded genetic algorithms with different crossover operator in noisy environment have been investigated.Results show the performance of deterministic crowding genetic algorithm and multi population genetic algorithm in the environment are better than that of elist genetic algorithm;the behaviors of alone point crossover outperform that of blended crossover.