摘要: 结合自组织迁移算法和社会认知优化的优点,在社会认知优化中融入自组织迁移的过程,通过增加2个参数协调两者的优化进程。经过大量的实验确定这2个参数的适当取值,完善了算法。该算法对最终的优化结果产生的影响微小,且在早期可以就获得较快的收敛 速度。
关键词:
演化计算,
社会认知优化,
自组织迁移算法
Abstract: To combine the advantages of Self-Organizing Migrating Algorithm(SOMA) and Society Cognitive Optimization(SCO), two parameters are used in the optimization to put SOMA process in SCO, resulting in a good improvement. Large number of experiments have been done and two parameters have been chosen which fit the algorithm most and perfect it. Although it causes a slight effect to the optimization solution, the improved optimization algorithm puts the convergence speed to a more quickly level.
Key words:
evolutionary computation,
Society Cognitive Optimization(SCO),
Self-Organizing Migrating Algorithm(SOMA)
中图分类号:
王玲娟;蔚承建;李承相. 用自组织迁移算法改进的社会认知优化算法[J]. 计算机工程, 2008, 34(22): 201-203.
WANG Ling-juan; WEI Cheng-jian; LI Cheng-xiang. Society Cognitive Optimization Algorithm Modified with Self-organizing Migrating Algorithm[J]. Computer Engineering, 2008, 34(22): 201-203.