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Orthogonal methods based ant colony search for solving continuous optimization problems

Hu, X., Zhang, J., and Li, Y. (2008) Orthogonal methods based ant colony search for solving continuous optimization problems. Journal of Computer Science and Technology, 23 (1). pp. 2-18. ISSN 1000-9000 (doi:10.1007/s11390-008-9111-5)

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Publisher's URL: http://dx.doi.org/10.1007/s11390-008-9111-5

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 e±ciently. 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 of API and CACO by testing seventeen functions in the continuous domain. The results demonstrate that the proposed COAC algorithm outperforms the others.

Item Type:Article
Status:Published
Refereed:Yes
Glasgow Author(s):Li, Prof Yun
Authors: Hu, X., Zhang, J., and Li, Y.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Research Group:Intelligent Systems
Journal Name:Journal of Computer Science and Technology
Publisher:Springer
ISSN:1000-9000
Copyright Holders:Copyright © 2008 Springer
First Published:First published in Engineering Applications of Artificial Intelligence 23(1):2-18
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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