Using artificial physics to solve global optimization problems

doi:10.1109/COGINF.2009.5250689

CORC > 兰州理工大学 > 兰州理工大学

	Using artificial physics to solve global optimization problems
	Xie, Liping 1,2; Zeng, Jianchao 2; Cui, Zhihua 2
	2009
会议日期	June 15, 2009 - June 17, 2009
会议地点	Kowloon, Hong Kong, Hong kong
关键词	Heuristic methods Potential energy Stochastic systems Experimental simulations Global optimization problems Newton's second law Objective functions Physicomimetics Stochastic global optimization User Defined Functions Virtual forces
DOI	10.1109/COGINF.2009.5250689
页码	502-508
英文摘要	Heuristics are quite an effective kind of methods to solve global optimization problems, which utilizes sample solution(s) searching the feasible regions of the problems in various intelligent ways. Inspired by physical rule, this paper proposes a stochastic global optimization algorithm based on Physicomimetics framework. In the algorithm, a population of sample individuals search a global optimum in the problem space driven by virtual forces, which simulate the process of the system continually evolving from initial higher potential energy to lower one until a minimum is reached. Each individual has a mass, position and velocity. The mass of each individual corresponds to a user-defined function of the value of an objective function to be optimized. An attraction-repulsion rule is constructed and used to move individuals towards the optimality. Experimental simulations show that the algorithm is effective. © 2009 IEEE.
会议录	Proceedings of the 2009 8th IEEE International Conference on Cognitive Informatics, ICCI 2009
会议录出版者	IEEE Computer Society
语种	英语
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117037]
专题	兰州理工大学
作者单位	1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China; 2.Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, shanxi, China
推荐引用方式 GB/T 7714	Xie, Liping,Zeng, Jianchao,Cui, Zhihua. Using artificial physics to solve global optimization problems[C]. 见:. Kowloon, Hong Kong, Hong kong. June 15, 2009 - June 17, 2009.