Abstract
In the last half century, computer science has witnessed the appearance of nature-inspired methods for the resolution of complex optimization problems, which are hardly solved by traditional optimization methods. Metaheuristics like evolutionary algorithms or swarm intelligence have been successfully applied to a wide range of both theoretical and practical problems.
This article presents a new optimization method based in reproduction mechanics of plant clonal colonies. These systems are composed of a set of clones, interconnected and spatially spread over a geographical area. In this new metaheuristic, called Clonal Colony Optimization (CCO), problem solutions are associated to clones, that are subject to evolutionary cycles that adaptively reconfigure the geographical covering over the search space of the problem. Solutions coded in this manner would be more robust that those obtained using independent individuals.
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Maturana, J., Vergara, F. (2011). Robust Optimization by Means of Vegetative Reproduction. In: Bouchachia, A. (eds) Adaptive and Intelligent Systems. ICAIS 2011. Lecture Notes in Computer Science(), vol 6943. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23857-4_39
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DOI: https://doi.org/10.1007/978-3-642-23857-4_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23856-7
Online ISBN: 978-3-642-23857-4
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