Abstract
In engineering as well as in non-engineering areas, numerous optimisation problems have to be solved using a wide range of optimisation methods. Soft-computing optimisation procedures are often applied to problems for which the classic mathematical optimisation approaches do not yield satisfactory results. In this paper we present a relatively new optimisation algorithm denoted as HC12 and demonstrate its possible parallel implementation. The paper aims to show that HC12 is highly scalable and can be implemented in a cluster of computers. As a practical consequence, the high scalability substantially reduces the computing time of optimisation problems.
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Matousek, R. (2010). HC12: Highly Scalable Optimisation Algorithm. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Studies in Computational Intelligence, vol 284. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12538-6_15
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DOI: https://doi.org/10.1007/978-3-642-12538-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12537-9
Online ISBN: 978-3-642-12538-6
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