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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/26111
- The accumulated experience ant colony for the travelling salesman problem
- Randall, Marcus; Montgomery, James
- Ant 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.
- Publication type
- Journal article
- International Journal of Computational Intelligence and Applications, Vol. 3, no. 2 (June 2003), p. 189-198
- Publication year
- Ant colony optimisation; Computer science; Travelling salesman problem
- Imperial College Press
- Publisher URL
- Copyright © 2003 Imperial College Press. Publisher does not officially support author/institution self-archiving of either the postprint (final, revised accepted draft) or published version of full text.
- Peer reviewed