A Parallel Implementation of Ant Colony Optimization

Randall, M; Lewis, A

doi:10.1006/jpdc.2002.1854

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Author(s)

Randall, M

Lewis, A

Griffith University Author(s)

Lewis, Andrew J.

Year published

2002

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Abstract

Ant Colony Optimization is a relatively new class of meta-heuristic search techniques for optimization problems. As it is a population-based technique that examines numerous solution options at each step of the algorithm, there are a variety of parallelization opportunities. In this paper, several parallel decomposition strategies are examined. These techniques are applied to a specific problem, namely the travelling salesman problem, with encouraging speedup and efficiency results.Ant Colony Optimization is a relatively new class of meta-heuristic search techniques for optimization problems. As it is a population-based technique that examines numerous solution options at each step of the algorithm, there are a variety of parallelization opportunities. In this paper, several parallel decomposition strategies are examined. These techniques are applied to a specific problem, namely the travelling salesman problem, with encouraging speedup and efficiency results.
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Journal Title

Journal of Parallel and Distributed Computing

Volume

DOI

https://doi.org/10.1006/jpdc.2002.1854

Copyright Statement

© 2002 Elsevier. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.

Subject

Distributed computing and systems software

Publication URI

http://hdl.handle.net/10072/6633

Collection

Journal articles