Improved Self-adaptive Control Parameter of Differential Evolution for Global Optimization
Zhou Cui-hong · Microcomputer Information · 2010
Differential evolution(DE) is a new heuristic global searchig technique based on population which has been found to be very robust for real parameter's optimization.In order to accelerate the convergence speed of DE algorithm in optimal searching and to overcome the premature convergence which is frequently existed in heuristic algorithms,in this paper,we propose an improved selfadaptive differential evolution,referred to as ISADE.Experimental results indicate that the performance of the ISADE outperforms other evolutionary algorithms in terms of the quality of the final solution and the stability;and its computational cost is lower than the cost required by the other techniques compared.