Continuous function optimization using hybrid ant colony approach with orthogonal design scheme

Zhang, J., Chen, W., Zhong, J., Tan, X. and Li, Y. (2006) Continuous function optimization using hybrid ant colony approach with orthogonal design scheme. Lecture Notes in Computer Science, 4247, pp. 126-133. (doi: 10.1007/11903697_17)

Abstract

A hybrid Orthogonal Scheme Ant Colony Optimization (OSACO) algorithm for continuous function optimization (CFO) is presented in this paper. The methodology integrates the advantages of Ant Colony Optimization (ACO) and Orthogonal Design Scheme (ODS). OSACO is based on the following principles: a) each independent variable space (IVS) of CFO is dispersed into a number of random and movable nodes; b) the carriers of pheromone of ACO are shifted to the nodes; c) solution path can be obtained by choosing one appropriate node from each IVS by ant; d) with the ODS, the best solved path is further improved. The proposed algorithm has been successfully applied to 10 benchmark test functions. The performance and a comparison with CACO and FEP have been studied.

• Item Type: Articles
• Additional Information: The original publication is available at www.springerlink.com
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Li, Professor Yun
• Authors: Zhang, J., Chen, W., Zhong, J., Tan, X., and Li, Y.
• Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering; Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Research Group: Intelligent Systems
• Journal Name: Lecture Notes in Computer Science
• Publisher: Springer
• ISSN: 0302-9743
• Copyright Holders: Copyright © 2006 Springer
• First Published: First published in Lecture Notes in Computer Science 4247:126-133
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.