Differential evolution algorithm with hybrid wave
混合波动差分进化算法*

Traditional differential evolution algorithm in dealing with complicated optimization problems has shortcomings, such as being trapped into local optimum easily and low solution precision. This paper proposed a new hybrid differential evolution algorithm with dynamic wave. Two predetermined parameters sets, which were distinguished by hybrid factors to generate fluctuation mutation and crossover rate, were selected each in turn. At the same time, to enhance the convergent rate, randomly selected vectors with the optimal fitness values we introduced to guide searching direction. Used Benchmark problems to verify this algorithm and the result of simulation, which was compared to other well-known algorithms. It indicates that this algorithm is better than several other algorithms both in convergence rate and quality of optimization.