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Bi-Criterion Optimization with Multi Colony Ant Algorithms

  • Steffen Iredi
  • Daniel Merkle
  • Martin Middendorf
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1993)

Abstract

In this paper we propose a new approach to solve bi-criterion optimization problems with ant algorithms where several colonies of ants cooperate in finding good solutions. We introduce two methods for cooperation between the colonies and compare them with a multistart ant algorithm that corresponds to the case of no cooperation. Heterogeneous colonies are used in the algorithm, i.e. the ants differ in their preferences between the two criteria. Every colony uses two pheromone matrices — each suitable for one optimization criterion. As a test problem we use the Single Machine Total Tardiness problem with changeover costs.

Keywords

Pareto Front Total Tardiness Global Good Solution Changeover Cost Pheromone Matrice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Steffen Iredi
    • 1
  • Daniel Merkle
    • 1
  • Martin Middendorf
    • 1
  1. 1.Institute AIFBUniversity of KarlsruheKarlsruheGermany

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