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- Title
- Higher order pheromone models in ant colony optimisation
- Author(s)
- Montgomery, James
- Abstract
- Ant colony optimisation is a constructive metaheuristic that successively builds solutions from problem-specific components. A parameterised model known as pheromone-an analogue of the trail pheromones used by real ants-is used to learn which components should be combined to produce good solutions. In the majority of the algorithm's applications a single parameter from the model is used to influence the selection of a single component to add to a solution. Such a model can be described as first order. Higher order models describe relationships between several components in a solution, and may arise either by contriving a model that describes subsets of components from a first order model or because the characteristics of solutions modelled naturally relate subsets of components. This paper introduces a simple framework to describe the application of higher order models as a tool to understanding common features of existing applications. The framework also serves as an introduction to those new to the use of such models. The utility of higher order models is discussed with reference to empirical results in the literature.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies
- Source
- Lecture Notes in Computer Science : Proceedings 5th International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS 2006), Brussels, Belgium, 04-07 September 2006, Vol. 4150, p. 428-435
- Publication year
- 2006
- Keyword(s)
- ACO; Ant colony optimisation; Model-based search; Pheromone model
- Publisher
- Springer-Verlag
- ISBN
- 9783540384823
- Publisher URL
- http://dx.doi.org/10.1007/11839088_42
- Copyright
- Copyright © Springer-Verlag Berlin Heidelberg 2006. The author's final draft of this paper is reproduced here in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com.
- Full text
- Peer reviewed
