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Issue:
Particle swarm algorithm based on simulated annealing to solve constrained optimization
Author(s):
Kou Xiao-Li
,
Liu San-yang
Pages:
136
-
140
Year:
2007
Issue:
1
Journal:
JOURNAL OF JILIN UNIVERSITY ENGINEERING AND TECHNOLOGY EDITION
Keyword:
人工智能
;
粒子群算法
;
模拟退火
;
约束优化问题
;
双群体
;
多样性
;
Abstract:
针对复杂约束优化问题,提出一种基于模拟退火(SA)的粒子群(PSO)算法(SAPSO).该算法使粒子的飞行无记忆性,结合模拟退火算法重新生成停止进化粒子的位置,增强了全局搜索能力.同时采用双群体搜索机制,一个群体保存具有可行解的粒子,用SAPSO算法使粒子逐步搜索到最优可行解;另一个群体保存具有不可行解的粒子,并且可行解群体以一定的概率接受具有不可行解的粒子,有效地维持了群体的多样性.仿真结果表明:该算法能够快速准确地找到位于约束边界上(或附近)的最优解,具有较好的稳定性.
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