摘要：The Differential Evolutionary algorithm (DE) is awell-known and effective metaheuristic method for continuousoptimization problems. However, due to contractionstagnation and early convergence problems, the performanceof the DE algorithm can be influenced at the convergencespeed and optimization accuracy. Therefore, this paperproposes an improved DE algorithm with the Levy flightsmechanism and the Simulated Annealing algorithm (SA),namely DESA-LF algorithm, which effectively uses theadvantages of them with generating the better candidatesolutions to reduce the convergence speed for making theoptimal solution towards the global optimal direction. Finally,we use six typical functions with different complexities andmake the comparisons with the DE algorithm, the DE-LFalgorithm and other meta-heuristic algorithms to verify theefficient of DESA-LF. From the results and convergencecurves, the DESA-LF has the advantages of extending theconvergence speed and enhancing the optimization accuracy.Therefore, it demonstrates that convergence speed andoptimization accuracy of DESA-LF are highly efficient andsuperior.
关键词：Differential Evolutionary algorithm; Simulated Annealing algorithm; Levy Flights mechanism; function optimization problem
