Differential evolution algorithm with different strategies and control parameters
Shuangzi Sun · Journal of Computer Applications · 2011
An improved Differential Evolution(DE) algorithm was proposed to solve the problem of premature convergence and improve the computational efficiency of DE.Firstly,different strategies with different parameter values were adopted to enrich the population diversity.Secondly,a new evaluation index was established to determine the suitable combination to match different phases of the search process.Finally,the evolution process was divided into many subprocesses to eliminate the negative effect of the previously selected combination.The contrast experimental results on ten classical Benchmark functions show that the proposed algorithm has a relatively better performance.