Abstract
This paper introduces SASS2, a novel control parameter free optimization algorithm, which combines a population based self-adaptive Hill-Climbing strategy with a stopping criterion and a heuristic for selecting the population size for the hill-climbing component. Experiments presented in this paper demonstrate that the algorithm is very effective and also very efficient whilst removing the need for tuning the algorithm to match an optimization problem at hand. This provides practitioners with a powerful tool, which can be used as a black-box optimizer by an end-user without the need to become an expert in optimization algorithms.
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© 2009 Springer-Verlag London Limited
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Nolle, L. (2009). On a Control Parameter Free Optimization Algorithm. In: Bramer, M., Petridis, M., Coenen, F. (eds) Research and Development in Intelligent Systems XXV. SGAI 2008. Springer, London. https://doi.org/10.1007/978-1-84882-171-2_9
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DOI: https://doi.org/10.1007/978-1-84882-171-2_9
Publisher Name: Springer, London
Print ISBN: 978-1-84882-170-5
Online ISBN: 978-1-84882-171-2
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