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Anti-pheromone as a tool for better exploration of search space

Citation

Montgomery, J and Randall, M, Anti-pheromone as a tool for better exploration of search space, Proceedings of the 3rd International Workshop on Ant Algorithms (ANTS 2002), 12-14 September 2002, Brussels, Belgium, pp. 100-110. ISBN 978-3-540-44146-5 (2002) [Refereed Conference Paper]


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Copyright Statement

Copyright 2002 Springer-Verlag Berlin Heidelberg

DOI: doi:10.1007/3-540-45724-0_9

Abstract

Many animals use chemical substances known as pheromones to induce behavioural changes in other members of the same species. The use of pheromones by ants in particular has lead to the development of a number of computational analogues of ant colony behaviour including Ant Colony Optimisation. Although many animals use a range of pheromones in their communication, ant algorithms have typically focused on the use of just one, a substance that encourages succeeding generations of (artificial) ants to follow the same path as previous generations. Ant algorithms for multi-objective optimisation and those employing multiple colonies have made use of more than one pheromone, but the interactions between these different pheromones are largely simple extensions of single criterion, single colony ant algorithms. This paper investigates an alternative form of interaction between normal pheromone and anti-pheromone. Three variations of Ant Colony System that apply the anti-pheromone concept in different ways are described and tested against benchmark travelling salesman problems. The results indicate that the use of anti-pheromone can lead to improved performance. However, if anti-pheromone is allowed too great an influence on antsí decisions, poorer performance may result.

Item Details

Item Type:Refereed Conference Paper
Keywords:ant colony optimisation, solution representation, search space, optimisation
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Neural, Evolutionary and Fuzzy Computation
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Information and Computing Sciences
Author:Montgomery, J (Dr James Montgomery)
ID Code:97260
Year Published:2002
Deposited By:Information and Communication Technology
Deposited On:2014-12-09
Last Modified:2016-01-18
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