摘要
利用粒子群多样性的反馈信息,给出带有粒子群多样性测度反馈控制的新惯性权值动态自适应调节方法,有效地维持进化初期的种群多样性,降低粒子群优化算法在进化初期发生早熟的风险,提高最优化解的精度,减小种群规模对优化精度的影响。几个典型函数的仿真结果以及与2种典型的惯性权值调节粒子群算法的比较结果表明了算法的有效性。
A new method of adjusting inertial weight adaptively with diversity feedback control is proposed. The diversity of swarm is maintained especially in the early phase of iterations. The risk of premature convergence is reduced and the precision of the optimum is improved remarkably, the influence of the swarm size on an optimum is weakened. The efficiency of the algorithm is verified by the simulation results of three benchmark functions and the comparison with two adaptive inertial weight Particle Swarm Optimization（PSO） algorithms.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第22期202-204,共3页
Computer Engineering
关键词
粒子群优化
多样性
惯性权值
Particle Swarm Optimization（PSO）： diversity： inertial weight
