A robust adaptive hybrid genetic simulated annealing algorithm for the global optimization of multimodal functions

doi:10.1109/CCDC.2011.5968132

	A robust adaptive hybrid genetic simulated annealing algorithm for the global optimization of multimodal functions
	Xu, Qiaoling 1; Zhang, Gongwang 2; Zhao, Chao 2; An, Aimin 3
	2011
关键词	Global optimization Iterative methods Local search (optimization) Simulated annealing Adaptive scheme Complex optimization problems Genetic simulated annealing Genetic simulated annealing algorithms Global searching ability Hill climbing Hybrid genetic algorithms Local search techniques
DOI	10.1109/CCDC.2011.5968132
页码	7-12
英文摘要	In this paper we presented a novel hybrid genetic algorithm for solving NLP problems based on combining the Genetic algorithm and Simulated annealing, together with a local search strategy. The proposed hybrid approach combines the merits of genetic algorithm (GA) with simulated annealing (SA) to construct a more efficient genetic simulated annealing (GSA) algorithm for global search, which could well maintain the population diversity in GA evolution without becoming easily trapped in local optimum. The iterative hill climbing (IHC) method as a local search technique is incorporated into GSA loop to speed up the convergence of the algorithm. In addition, a self-adaptive hybrid mechanism is developed to maintain a tradeoff between the global and local optimizer searching then to efficiently locate quality solution to complex optimization problem. The computational results indicate that the global searching ability and the convergence speed of this hybrid algorithm are significantly improved. Some well-known benchmark functions are utilized to test the applicability of the proposed algorithm. © 2011 IEEE.
会议录	Proceedings of the 2011 Chinese Control and Decision Conference, CCDC 2011
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/116700]
专题	电气工程与信息工程学院
作者单位	1.Faculty of College of Chemistry and Chemical Engineering, FuZhou University, FuZhou, 350108, China; 2.College of Chemistry and Chemical Engineering, FuZhou University, FuZhou, 350108, China; 3.Faculty of School of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou, Gansu 730050, China
推荐引用方式 GB/T 7714	Xu, Qiaoling,Zhang, Gongwang,Zhao, Chao,et al. A robust adaptive hybrid genetic simulated annealing algorithm for the global optimization of multimodal functions[C]. 见:.