Abstract
Applying evolutionary algorithms based on populations of trial points is attractive in many fields nowadays. Apart from the evolutionary analogy, profound analysis on their performance is lacking. In this paper, within a framework to study the behaviour of algorithms, an analysis is given on the performance of Controlled Random Search (CRS), a simple population based Global Optimization algorithm. The question is for which functions (cases) and which parameter settings the algorithm is effective and how the efficiency can be influenced. For this, several performance indicators are described. Analytical and experimental results on effectiveness and speed of convergence (Success Rate) of CRS are presented.
This work was supported by the Ministry of Education of Spain (CICYT TIC99-0361).
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© 2002 Kluwer Academic Publishers
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Hendrix, E.M.T., Ortigosa, P.M., Garcia, I. (2002). On the Efficiency and Effectiveness of Controlled Random Search. In: Dzemyda, G., Šaltenis, V., Žilinskas, A. (eds) Stochastic and Global Optimization. Nonconvex Optimization and Its Applications, vol 59. Springer, Boston, MA. https://doi.org/10.1007/0-306-47648-7_8
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DOI: https://doi.org/10.1007/0-306-47648-7_8
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