Abstract
This paper presents how the Ant Colony Optimization (ACO) metaheuristic can be extended to continuous search domains and applied to both continuous and mixed discrete-continuous optimization problems. The paper describes the general underlying idea, enumerates some possible design choices, presents a first implementation, and provides some preliminary results obtained on well-known benchmark problems. The proposed method is compared to other ant, as well as non-ant methods for continuous optimization. © 2004 Springer-Verlag.
Cite
CITATION STYLE
Socha, K. (2004). ACO for continuous and mixed-variable optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3172 LNCS, pp. 25–36). Springer Verlag. https://doi.org/10.1007/978-3-540-28646-2_3
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