嵌入模拟退火机制的免疫逃避的粒子群算法  

Escape from the immune particle swarm algorithm embedded mechanism of simulated annealing

作　　者：刘微[1] 孙榕彬 王洪瑞[1] 

机构地区：[1]吉林师范大学信息技术学院,吉林四平136000

出　　处：《吉林师范大学学报（自然科学版）》2018年第1期85-90,共6页Journal of Jilin Normal University:Natural Science Edition

基　　金：国家自然科学基金项目(61305082)

摘　　要：在寻优过程中,为了能够更快速的找到最优解,提出了一种基于免疫逃避粒子群算法与模拟退火粒子群算法相结合的改进算法.模拟退火粒子群算法能够使算法跳出局部极值,免疫逃避粒子群算法能够让初始化粒子更加快速的搜索,二者的结合让两个算法的优越性更加突出,搜索速度更快,收敛和搜索精度都更加优化.In the process of optimization,an improved algorithm based on Immune Evasion Particle Swarm Optimization and Simulated Annealing Particle Swarm Optimization was proposed in order to find the optimal solution faster. Simulated Annealing Particle Swarm algorithm made the algorithm to jump out of local extremum,and Immune Escape Particle Swarm algorithm made the searching of the initialization particle more quickly. The advantages of the combination for the two algorithms were more prominent,faster searching speed,more optimal convergence and searching precision.

关 键 词：免疫逃避 粒子群算法 模拟退火 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]