摘要
针对具有复杂约束条件的优化问题,提出了一种混合粒子群算法。该混合算法在将标准粒子群算法与线性搜索法有机结合的基础上,依次对粒子的每一维变量进行适当变化并同时判断其变化的效果。最后进行了数值实验,其结果表明,所提出的混合粒子群算法对于具有复杂有约束条件的优化问题有较好的优化效果。
Focused on the study of the optimization problem with complicated constraint condition,this paper proposed the hybrid particle swarm optimization （ PSO） algorithm. Firstly,flexibly combined the standard PSO algorithm with the line search method. Then,adaptively and respectively modified each variable of the particle and gave the searching result simultaneously. Finally,gave the digit experiment. The result shows the proposed hybrid PSO algorithm can obtain a satisfied result for the optimization problem with complicated constraint condition.
出处
《计算机应用研究》
CSCD
北大核心
2010年第9期3256-3258,3267,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(60702076)
湖南省自然科学基金资助项目(07JJ6109)
关键词
复杂约束条件
混合粒子群算法
线性搜索
变量
综合信息
complicated constraint condition
hybrid particle swarm optimization
line search
variables
synthetical information
