动态环境下的种群扩散粒子群优化算法

Population Diffuse PSO Algorithm in Dynamic Environment

传统的粒子群优化算法在优化过程中难以有效地监测环境的动态变化和响应。针对上述问题,通过增加外围监测粒子加强监测有效性,提出一种可以动态响应环境变化的种群多样性扩散函数,在此基础上设计一种扩散粒子群优化算法(DPSO),在动态环境中与APSO、CPSO进行比较,实验结果表明,DPSO可以更有效地跟踪动态环境下极值的变化并快速收敛。

It is difficult for PSO to detect dynamic change of environment and response in optimizing process.Aiming at the problems,by adding particles which are on the periphery for detecting the change of environment,this paper proposes a new diffuse population function to respond change,and designs an algorithm named Diffuse Particle Swarm Optimization（DPSO）.Comparison with APSO and CPSO,it can detect changes of environment more effectively and track with optimum solution faster.