摘要
多目标优化问题中的一个关键在于合理地评判各有效解的优劣。通过引入灰色系统理论中灰色关联度的概念作为评判准则,结合粒子群优化算法进行有约束多目标规划问题的研究。提出了一种新的不可行解的保留策略,进化过程中以此策略保留适量的不可行解,有利于增强对约束边界附近可能的最优解的搜索,同时,针对粒子群优化算法的容易陷入局部最优的缺点,实现了以粒子群优化为载体的混合算法:即对全局极值邻域进一步混沌搜索寻优。仿真结果表明改进的算法对多目标决策问题是有效的。
It is unfathomed to assess the non-inferior solutions of the multi-objective optimization. The gray cognate is referred as a criterion in this restricted multi-objective optimization. A new strategy to keep some infeasible individuals in the swarm is proposed in order to enhance the capability of searching in the edge of the restriction. A hybrid chaos searching method based on PSO is adopted to ensure globalconvergence. The simulation shows that this improved algorithm is effective in multi-objective decision.
出处
《火力与指挥控制》
CSCD
北大核心
2010年第1期77-80,共4页
Fire Control & Command Control
基金
空军重点科研项目基金(KJ06090)
关键词
多目标决策
粒子群优化
不可行解
混沌搜索
灰色关联
multi-objective decision, particle swarm optimization, non-inferior solutions, chaos searching, gray cognate
