On the behavior of ACO algorithms: studies on simple problems

Authors:
Daniel Merkle;Martin Middendorf
Affiliations:
Department of Computer Science, University of Leipzig, D-04109 Leipzig, Germany;Department of Computer Science, University of Leipzig, D-04109 Leipzig, Germany
Venue:
Metaheuristics
Year:
2004

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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.