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The accumulated experience ant colony for the travelling salesman problem
journal contribution
posted on 2023-05-18, 05:46 authored by Erin MontgomeryErin Montgomery, Randall, MAnt colony optimization techniques are usually guided by pheromone and heuristic cost information when choosing the next element to add to a solution. However, while an individual element may be attractive, usually its long term consequences are neither known nor considered. For instance, a short link in a traveling salesman problem may be incorporated into an ant's solution, yet, as a consequence of this link, the rest of the path may be longer than if another link was chosen. The Accumulated Experience Ant Colony uses the previous experiences of the colony to guide in the choice of elements. This is in addition to the normal pheromone and heuristic costs. Two versions of the algorithm are presented, the original and an improved AEAC that makes greater use of accumulated experience. The results indicate that the original algorithm finds improved solutions on problems with less than 100 cities, while the improved algorithm finds better solutions on larger problems.
History
Publication title
International Journal of Computational Intelligence and ApplicationsPagination
189-198ISSN
1469-0268Department/School
School of Information and Communication TechnologyPublisher
Imperial College PressPlace of publication
United KingdomRights statement
c World Scientific Publishing CompanyRepository Status
- Restricted