A Cooperative Optimization Algorithm Based on Gaussian Process and Particle Swarm Optimization for Optimizing Expensive Problems

doi:10.1109/CSO.2009.263

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	A Cooperative Optimization Algorithm Based on Gaussian Process and Particle Swarm Optimization for Optimizing Expensive Problems
	Su, Guoshao 1; Jiang, Quan 2
	2009
会议日期	APR 24-26, 2009
会议地点	Sanya, PEOPLES R CHINA
DOI	10.1109/CSO.2009.263
页码	929
英文摘要	In many engineering optimization problems, like design optimization or structure parameters identification, fitness evaluation is very expensive and time consuming. This problem limited the applications of standard evolutionary computation methods in real-world engineering. A cooperative optimization algorithm (GP-PSO) based on Gaussian process (GP) machine learning and Particle Swarm Optimization (PSO) algorithm is presented in this paper for solving computationally expensive optimization problem. Gaussian process is used to predict the most promising solutions before searching the global optimum solution using PSO during each iteration step. The study result indicates GP-PSO algorithm clearly outperforms standard PSO algorithm with much less fitness evaluations on benchmark functions. The result of application to a real-world engineering problem also suggests that the proposed optimization framework is capable of solving computationally expensive optimization problem effectively.
会议录	INTERNATIONAL JOINT CONFERENCE ON COMPUTATIONAL SCIENCES AND OPTIMIZATION, VOL 2, PROCEEDINGS
会议录出版者	IEEE COMPUTER SOC
会议录出版地	LOS ALAMITOS
语种	英语
WOS研究方向	Computer Science ; Operations Research & Management Science
WOS记录号	WOS:000273549700210
内容类型	会议论文
源URL	[http://119.78.100.198/handle/2S6PX9GI/4534]
专题	岩土力学所知识全产出_会议论文
作者单位	1.Guangxi Univ, Dept Civil & Architecture Engn; 2.Chinese Acad Sci, Inst Rock & Soil Mech
推荐引用方式 GB/T 7714	Su, Guoshao,Jiang, Quan. A Cooperative Optimization Algorithm Based on Gaussian Process and Particle Swarm Optimization for Optimizing Expensive Problems[C]. 见:. Sanya, PEOPLES R CHINA. APR 24-26, 2009.