A self-adaptive differential evolution algorithm for binary CSPs

作者：Fu Hongjie; Ouyang Dantong^*; Xu Jiaming

来源：Computers & Mathematics with Applications, 2011, 62(7): 2712-2718.

DOI：10.1016/j.camwa.2011.06.053

• Differential evolution
• Self-adaptive
• CSPs

A novel self-adaptive differential evolution (SADE) algorithm is proposed in this paper. SADE adjusts the mutation rate F and the crossover rate CR adaptively, taking account of the different distribution of population. In order to balance an individual's exploration and exploitation capability for different evolving phases, F and CR are equal to two different self-adjusted nonlinear functions. Attention is concentrated on varying F and CR dynamically with each generation evolution. SADE maintains the diversity of population and improves the global convergence ability. It also improves the efficiency and success rate and avoids the premature convergence. Simulation and comparisons based on test-sets of CSPs demonstrate the effectiveness, efficiency and robustness of the proposed algorithm.

• 出版日期2011-10
• 单位吉林大学; 中国科学院计算机网络信息中心