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ACO for Continuous and Mixed-Variable Optimization

  • Krzysztof Socha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3172)

Abstract

This paper presents how the Ant Colony Optimization (ACO) metaheuristic can be extended to continuous search domains and applied to both continuous and mixed discrete-continuous optimization problems. The paper describes the general underlying idea, enumerates some possible design choices, presents a first implementation, and provides some preliminary results obtained on well-known benchmark problems. The proposed method is compared to other ant, as well as non-ant methods for continuous optimization.

Keywords

Probability Density Function Continuous Optimization Continuous Domain Normal Probability Density Function Future Generation Computer System 
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 2004

Authors and Affiliations

  • Krzysztof Socha
    • 1
  1. 1.IRIDIAUniversité Libre de BruxellesBrusselsBelgium

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