Abstract
The behavior of Ant Colony Optimization (ACO) algorithms is studied on simple problems which allow us to identify characteristic properties of these algorithms. In particular, ACO algorithms using different pheromone evaluation methods are investigated. A new method for the use of pheromone information by artificial ants is proposed. Experimentally it is shown that an ACO algorithm using the new method performs better than ACO algorithms using other known methods for certain types of problems.
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Merkle, D., Middendorf, M. (2003). On the Behavior of ACO Algorithms: Studies on Simple Problems. In: Metaheuristics: Computer Decision-Making. Applied Optimization, vol 86. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4137-7_22
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DOI: https://doi.org/10.1007/978-1-4757-4137-7_22
Publisher Name: Springer, Boston, MA
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