On the Behavior of ACO Algorithms: Studies on Simple Problems

  • Daniel Merkle
  • Martin Middendorf
Part of the Applied Optimization book series (APOP, volume 86)


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.


Ant colony optimization Pheromone information Permutation problems. 


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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Daniel Merkle
    • 1
  • Martin Middendorf
    • 1
  1. 1.Department of Computer ScienceUniversity of LeipzigLeipzigGermany

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