基于SQP 局部搜索的混沌粒子群优化算法.pdf

第第第27卷第4期 Vol. 27 No. 4 控制与决策 Control and Decision 2012年4月 Apr. 2012 基于SQP局部搜索的混沌粒子群优化算法文章编号:1001-0920 (2012) 04-0557-05 徐文星 1,耿志强 1,朱群雄 1,顾祥柏 1,2 (,北京100029;,北京100029) 摘 要:提出一种基于序贯二次规划(SQP)法的混沌粒子群优化方法(CPSO-SQP).将混沌PSO作为全局搜索器,并用SQP加速局部搜索,使得粒子能够在快速局部寻优的基础上对整个空间进行搜索,既保证了算法的收敛性,,算法精度高、成功率大、全局收敛速度快,(HDPE)装置串级反应过程的乙烯单耗优化,根据工业反应机理以及现场操作经验分析可知,所提出的算法是可行的. 关键词:粒子群优化;序贯二次规划;混沌映射;非线性约束优化中图分类号:TP18;; 文献标识码:A Chaos particle swarm optimization algorithm integrated with sequential quadratic programming local search XU Wen-xing 1,GENG Zhi-qiang 1,ZHU Qun-xiong 1,GU Xiang-bai 1,2 (1. School of Information Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China; 2. Sinopec Engineering,Beijing 100029,:ZHU Qun-xiong,E-mail:******@.) Abstract:::Asequential quadratic programming integrated particle swarm optimization algorithm (CPSO-SQP) is proposed. This newalgorithm uses CPSO, which makes the best of ergodicity of chaos mapping, as the global optimizer while the SQP is employed for accelerating the local search. Thus, the particles are able to search the whole space while ?nding local optima fast, which increases the possibility of exploring a global optimum in problems with more local optima while ensuring the convergence of algorithm. The simulation