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A New Ant Colony Algorithm Using the Heterarchical Concept Aimed at Optimization of Multiminima Continuous Functions

  • Johann Dréo
  • Patrick Siarry
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2463)

Abstract

Ant colony algorithms are a class of metaheuristics which are inspired from the behaviour of real ants. The original idea consisted in simulating the trail communication, therefore these algorithms are considered as a form of adaptive memory programming. A new formalization is proposed for the design of ant colony algorithms, introducing the biological notions of heterarchy and communication channels.

Keywords

Particle Swarm Optimization Communication Channel Pheromonal Trail Analytical Test Function Biological Notion 
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 2005

Authors and Affiliations

  • Johann Dréo
    • 1
  • Patrick Siarry
    • 1
  1. 1.Laboratoire d’Étude et de Recherche en Instrumentation Signaux et Systèmes (L.E.R.I.S.S.)Université de Paris XII Val-de-MarneCréteilFrance

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