DACCO: a discrete ant colony algorithm to cluster geometry optimization
Pages 41 - 48
Abstract
We present a discrete ant colony algorithm to cluster geometry optimization. To deal with this continuous problem, the optimization framework includes functions to map solutions across the discrete and continuous spaces. Results obtained with short-ranged Morse clusters show that the proposed approach is effective, scalable and is competitive with state-of the-art optimization methods specifically designed to tackle continuous domains. A detailed analysis is presented to help to gain insight into the role played by several components of the ant colony algorithm.
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Index Terms
- DACCO: a discrete ant colony algorithm to cluster geometry optimization
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Published: 07 July 2012
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