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)

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

CLC Number: 

• TP312