SamACO: variable sampling ant colony optimization algorithm for continuous optimization

Hu, X., Zhang, J., Chung, H.S., Li, Y. and Liu, O. (2010) SamACO: variable sampling ant colony optimization algorithm for continuous optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 40(6), pp. 1555-1566. (doi: 10.1109/TSMCB.2010.2043094)

Abstract

An ant colony optimization (ACO) algorithm offers algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution constructions and to realize a pheromone laying-and-following mechanism. Although ACO is first designed for solving discrete (combinatorial) optimization problems, the ACO procedure is also applicable to continuous optimization. This paper presents a new way of extending ACO to solving continuous optimization problems by focusing on continuous variable sampling as a key to transforming ACO from discrete optimization to continuous optimization. The proposed SamACO algorithm consists of three major steps, i.e., the generation of candidate variable values for selection, the ants’ solution construction, and the pheromone update process. The distinct characteristics of SamACO are the cooperation of a novel sampling method for discretizing the continuous search space and an efficient incremental solution construction method based on the sampled values. The performance of SamACO is tested using continuous numerical functions with unimodal and multimodal features. Compared with some state-of-the-art algorithms, including traditional ant-based algorithms and representative computational intelligence algorithms for continuous optimization, the performance of SamACO is seen competitive and promising.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Li, Professor Yun
• Authors: Hu, X., Zhang, J., Chung, H.S., Li, Y., and Liu, O.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• Research Group: Systems Power and Energy
• Journal Name: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
• Publisher: Institute of Electrical and Electronics Engineers
• ISSN: 1083-4419
• ISSN (Online): 1941-0492
• Published Online: 05 April 2010
• Copyright Holders: Copyright © 2010 IEEE
• First Published: First published in IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 40(6):1555-1566
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher