Abstract
This paper presents a new mathematical approach to study the behaviour of population-based methods. The calculation of the takeover time and the dynamical growth curves is a common analytical approach to measure the selection pressure of an EA and any algorithm which manipulates a set of solutions. In this work, we propose a new and more accurate model to calculate these values. This new model also includes other very interesting features, such as the characterization of the complete behaviour of the methods using a single value, the Rayleigh distribution parameter. We also extend the study to consider the effect of the mutation (or in general, any neighborhood exploration operator) and we show several advanced uses of this models such as building self-adaptive techniques or comparing algorithms.
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Luque, G., Alba, E. (2012). Analyzing the Behaviour of Population-Based Algorithms Using Rayleigh Distribution. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32937-1_42
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DOI: https://doi.org/10.1007/978-3-642-32937-1_42
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