Abstract
The usual assumptions of the ant colony meta-heuristic are that each ant constructs its own complete solution and that it will then operate relatively independently of the rest of the colony (with only loose communications via the pheromone structure). However, a more aggressive approach is to allow some measure of competition amongst the ants. Two ways in which this can be done are to allow ants to take components from other ants or limit the number of ants that can make a particular component assignment. Both methods involve a number of competitions so that the probabilistic best assignment of component to ant can be made. Both forms of competitive ant colony optimisation outperform a standard implementation on the benchmark set of the assignment type problem, generalised assignment.
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Randall, M. (2007). Competitive Ant Colony Optimisation. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_97
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DOI: https://doi.org/10.1007/978-3-540-73325-6_97
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