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/lp/mit-press/ant-algorithms-for-discrete-optimization-0rfbNcfgoh
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- Publisher
- MIT Press
- Copyright
- © 1999 Massachusetts Institute of Technology
- ISSN
- 1064-5462
- eISSN
- 1530-9185
- DOI
- 10.1162/106454699568728
- Publisher site
- See Article on Publisher Site
Abstract
This article presents an overview of recent work on ant algorithms, that is, algorithms for discrete optimization that took inspiration from the observation of ant colonies' foraging behavior, and introduces the ant colony optimization (ACO) metaheuristic. In the first part of the article the basic biological findings on real ants are reviewed and their artificial counterparts as well as the ACO metaheuristic are defined. In the second part of the article a number of applications of ACO algorithms to combinatorial optimization and routing in communications networks are described. We conclude with a discussion of related work and of some of the most important aspects of the ACO metaheuristic.
Journal
Artificial Life – MIT Press
Published: Apr 1, 1999
Keywords: ant algorithms; ant colony optimization; swarm intelligence; metaheuristics; natural computation