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Ant Algorithms Solve Difficult Optimization Problems

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Advances in Artificial Life (ECAL 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2159))

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Abstract

The ant algorithms research field builds on the idea that the study of the behavior of ant colonies or other social insects is interesting for computer scientists, because it provides models of distributed organization that can be used as a source of inspiration for the design of optimization and distributed control algorithms. In this paper we overview this growing research field, giving particular attention to ant colony optimization, the currently most successful example of ant algorithms, as well as to some other promising directions such as ant algorithms inspired by labor division and brood sorting.

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Authors and Affiliations

  1. IRIDIA, Université Libre de Bruxelles, 50 Avenue F. Roosevelt, B-1050, Brussels, Belgium

    Marco Dorigo

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  1. Marco Dorigo
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Editors and Affiliations

  1. Faculty of Philosophy and Science Institute of Computer Science, Silesian University, 74601, Opava, Czech Republic

    Jozef Kelemen  & Petr Sosík  & 

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Dorigo, M. (2001). Ant Algorithms Solve Difficult Optimization Problems. In: Kelemen, J., Sosík, P. (eds) Advances in Artificial Life. ECAL 2001. Lecture Notes in Computer Science(), vol 2159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44811-X_2

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  • DOI: https://doi.org/10.1007/3-540-44811-X_2

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