| Title: | Automated selection of appropriate pheromone representations in ant colony optimization |
| Author(s): | Montgomery J; Randall M; Hendtlass T; |
| Address: | "Faculty of Information Technology, Bond University, QLD 4229, Australia. jmontgom@bond.edu.au" |
| ISSN/ISBN: | 1064-5462 (Print) 1064-5462 (Linking) |
| Abstract: | "Ant colony optimization (ACO) is a constructive metaheuristic that uses an analogue of ant trail pheromones to learn about good features of solutions. Critically, the pheromone representation for a particular problem is usually chosen intuitively rather than by following any systematic process. In some representations, distinct solutions appear multiple times, increasing the effective size of the search space and potentially misleading ants as to the true learned value of those solutions. In this article, we present a novel system for automatically generating appropriate pheromone representations, based on the characteristics of the problem model that ensures unique pheromone representation of solutions. This is the first stage in the development of a generalized ACO system that could be applied to a wide range of problems with little or no modification. However, the system we propose may be used in the development of any problem-specific ACO algorithm" |
| Keywords: | "Algorithms Animals Ants/*physiology Behavior, Animal/*physiology *Models, Biological Pheromones/*physiology *Selection, Genetic;" |
| Notes: | "MedlineMontgomery, James Randall, Marcus Hendtlass, Tim eng Review 2005/08/02 Artif Life. 2005 Summer; 11(3):269-91. doi: 10.1162/1064546054407149" |
