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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Amdahl, G.: Validity of the Single Processor Approach to Achieving Large-Scale Computing Capabilities. In: AFIPS Conference Proceedings, vol. (30), pp. 483–485 (1967)
Battiti, R., Tecchiolli, G.: Local search with memory: Benchmarking RTS. journal of Operations Research Spectrum 17(2/3), 67–86 (1995)
Matousek, R.: GA (GA with HC mutation) – implementation and application, Master thesis (in Czech), Brno University of Technology, Brno, Czech Republic (1995)
Matousek, R.: GAHC: A Hybrid Genetic Algorithm. In: Proceedings of the 10th Fuzzy Colloquium in Zittau, Zittau, pp. 239–244 (2002) ISBN: 3-9808089-2-0
Matousek, R.: GAHC: Improved Genetic Algorithm. In: Krasnogor, et al. (eds.) Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Springer book series, vol. 129, XIV, p. 114 (12p). Springer, Berlin (2008)
Mitchell, M., Holland, J.H.: When Will a Genetic Algorithm Outperform Hill Climbing? In: Cowan, J.D., Tesauro, G., Alspector, J. (eds.) Advances in Neural Information Processing Systems, vol. 6. Morgan Kaufmann, San Mateo (1994)
Zhou, R., Hansen, E.A.: Breadth-First Heuristic Search. In: 14th International Conference on Automated Planning and Scheduling (ICAPS 2004), Whister, British Columbia, Canada (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
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
Download citation
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
eBook Packages: EngineeringEngineering (R0)