Orthogonal Methods Based Ant Colony Search for Solving Continuous Optimization Problems |
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Authors: | Xiao-Min Hu Jun Zhang Yun Li |
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Affiliation: | (1) Department of Computer Science, Sun Yat-Sen University, Guangzhou, 510275, China;(2) Key Laboratory of Digital Life, (Sun Yat-Sen University), Ministry of Education, Guangzhou, 510275, China;(3) Department of Electronics and Electrical Engineering, University of Glasgow, Glasgow, G12 8LT, Scotland, UK |
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Abstract: | Research into ant colony algorithms for solving continuous optimization problems forms one of the most significant and promising
areas in swarm computation. Although traditional ant algorithms are designed for combinatorial optimization, they have shown
great potential in solving a wide range of optimization problems, including continuous optimization. Aimed at solving continuous
problems effectively, this paper develops a novel ant algorithm termed “continuous orthogonal ant colony” (COAC), whose pheromone
deposit mechanisms would enable ants to search for solutions collaboratively and effectively. By using the orthogonal design
method, ants in the feasible domain can explore their chosen regions rapidly and efficiently. By implementing an “adaptive
regional radius” method, the proposed algorithm can reduce the probability of being trapped in local optima and therefore
enhance the global search capability and accuracy. An elitist strategy is also employed to reserve the most valuable points.
The performance of the COAC is compared with two other ant algorithms for continuous optimization — API and CACO by testing
seventeen functions in the continuous domain. The results demonstrate that the proposed COAC algorithm outperforms the others.
Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.
Supported by the National Natural Science Foundation of China under Grant No. 60573066, the Guangdong Natural Science Foundation
Research under Grant No. 5003346, and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State
Education Ministry, P.R. China. |
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Keywords: | ant algorithm function optimization orthogonal design |
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