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Dynamic Optimization Through Continuous Interacting Ant Colony

  • Johann Dréo
  • Patrick Siarry
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3172)

Abstract

In recent past, optimization of dynamic problems has evoked the interest of the researchers in various fields which has resulted in development of several increasingly powerful algorithms. Unlike in static optimization, where the final goal is to find the fixed global optimum, in dynamic optimization the aim is to find and follow the evolution of the global optimum during the entire optimization time.

References

  1. 1.
    Branke, J.: Evolutionary Optimization in Dynamic Environments. Genetic Algorithms and Evolutionary Computation, vol. 3. Kluwer, Dordrecht (2001)Google Scholar
  2. 2.
    Dréo, J., Siarry, P.: Continuous Interacting Ant Colony Algorithm Based on Dense Heterarchy. Future Generation Computer Systems (2004) (to appear)Google Scholar
  3. 3.
    Xiong, Q., Jutan, A.: Continuous optimization using a dynamic simplex method. Chemical Engineering Science 58(16), 3817–3828 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

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

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