Adaptive evolutionary strategy based on feedback and chaotic mutation

In order to enhance the global searching ability and precision,this paper proposed an adaptive evolutionary strategy based on the feedback and chaos mutation(ESBFCM),in which the information of every generation's current optimal searching result and sharing degree was fed into the mutating formula.By tuning the variance of the mutation operator according to the feedback information,changed the mutation step of ES with the current searching result.And a part of individuals of the population in the searching procedure kept higher probability of jumping out the local minimum by the chaotic mutation.By these measures,enhanced the searching precision and the global searching ability.To compare the optimizing effect between traditional ES and the ESBFCM,the test based on three benchmarks were done,the test result demonstrates that the ESBFCM has higher the global searching ability and precision than the traditional ES.