期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 41, 期 5, 页码 2134-2143出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2013.09.012
关键词
Chemical reaction optimization; Particle swarm optimization
类别
资金
- National Natural Science Foundation of China [61173107]
- National High Technology Research and Development Program of China [2012AA01A301-01]
- Special Project on the Integration of Industry, Education and Research of Guangdong Province, China [2011A091000027]
- Project on the Integration of Industry, Education and Research of Huizhou, Guangdong Province, China [2012C050012012]
In this paper, a hybrid method for optimization is proposed, which combines the two local search operators in chemical reaction optimization with global search ability of for global optimum. This hybrid technique incorporates concepts from chemical reaction optimization and particle swarm optimization, it creates new molecules (particles) either operations as found in chemical reaction optimization or mechanisms of particle swarm optimization. Moreover, some technical bound constraint handling has combined when the particle update in particle swarm optimization. The effects of model parameters like InterRate, gamma, Inertia weight and others parameters on performance are investigated in this paper. The experimental results tested on a set of twenty-three benchmark functions show that a hybrid algorithm based on particle swarm and chemical reaction optimization can outperform chemical reaction optimization algorithm in most of the experiments. Experimental results also indicate average improvement and deviate over chemical reaction optimization in the most of experiments. (C) 2013 Elsevier Ltd. All rights reserved.
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