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Metaheuristics for Dynamic Optimization pp 189–210Cite as

Ant Colony Based Algorithms for Dynamic Optimization Problems

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 433))

Abstract

The use of metaheuristic approaches to deal with dynamic optimization problems has been largely studied, being evolutionary techniques the more widely used and assessed techniques. Nevertheless, successful applications coming from other nature-inspired metaheuristics, e.g., ant algorithms, have also shown their applicability in dynamic optimization problems, but received a limited attention until now. Different from perturbative techniques, ant algorithms use a set of agents which evolve in an environment to construct one solution. They cooperate by means of asynchronous communications based on numerical information laid on an environment. This environment is often modeled by a graph which constitutes a formalism with a great expressiveness, specially well-suited for dynamic optimization problems. A solution could be a structure like a subgraph, a route, a short path, a spanning tree, or even a partition of vertices. In this chapter we present a general overview of the more relevant works regarding the application of ant colony based algorithms for dynamic optimization problems. We will also highlight the mechanisms used in different implementations found in the literature, and thus show the potential of this kind of algorithms for research in this area.

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Author information

Authors and Affiliations

  1. Universidad Nacional de San Luis, Av. Ejército de Los Andes 950, 5700, San Luis, Argentina

    Guillermo Leguizamón

  2. Universidad de Málaga, Campus de Teatinos (3.2.12), Málaga, 29071, Spain

    Enrique Alba

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  1. Guillermo Leguizamón
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  2. Enrique Alba
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Correspondence to Guillermo Leguizamón .

Editor information

Editors and Affiliations

  1. , E.T.S.I. Informática (3-2-12), Universidad de Málaga, Málaga, 29071, Spain

    Enrique Alba

  2. , LISSI, Université Paris-Est Créteil, avenue du Général de Gaulle 61, Créteil, 94010, France

    Amir Nakib

  3. , Laboratoire LiSSi, Université Paris-Est Créteil Val de Marn, avenue du Général de Gaulle 61, Créteil, 94010, France

    Patrick Siarry

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Leguizamón, G., Alba, E. (2013). Ant Colony Based Algorithms for Dynamic Optimization Problems. In: Alba, E., Nakib, A., Siarry, P. (eds) Metaheuristics for Dynamic Optimization. Studies in Computational Intelligence, vol 433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30665-5_9

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  • DOI: https://doi.org/10.1007/978-3-642-30665-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30664-8

  • Online ISBN: 978-3-642-30665-5

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