Uniform differential evolution algorithm with transform function and performance analysis
具有转换函数的均匀差分进化算法及性能分析

When differential evolution algorithm is applied in complicated optimization problems, it has the shortages of prematurity and stagnation. By efficiently utilizing the information of objective function and solving problems, a uniform differential evolution algorithm with transform function is proposed in this paper. Firstly, three operators are designed to generate individuals which obey uniform distribution. Individuals can fully represent the solution space. So the diversity of populations and capability of global search will be enhanced. Secondly, a transform function used to simplify the objective function is constructed. It stretches the current local minimum and related regions up to a certain height, while keeps the optimized function unchanged under the local minimum. Thus, the number of local minima will be largely decreased with the progress of iterations. Finally, the improved algorithm is quantitatively evaluated by performance indices. The simulation results show that it has perfect property in efficacy and converges faster, and is more stable.