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A derivative-free filter driven multistart technique for global optimization
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Orientador(es)
Resumo(s)
A stochastic global optimization method based on a multistart strategy and a derivative-free filter local search for general constrained optimization is presented and analyzed. In the local search procedure, approximate descent directions for the constraint violation or the objective function are used to progress towards the optimal solution. The algorithm is able to locate all the local minima, and consequently, the global minimum of a multi-modal objective function. The performance of the multistart method is analyzed with a set of benchmark problems and a comparison is made with other methods.
Descrição
Palavras-chave
Global optimization Multistart, Descent direction Filter method
Contexto Educativo
Citação
Fernandes, Florbela P.; Costa, M. Fernanda P.; Fernandes, Edite M.G.P. (2012). A derivative-free filter driven multistart technique for global optimization. In Murgante, Beniamino (Eds.) 12th International Conference Salvador do Bahia, Computational Science and its Applications - ICCSA 2012, Part III, 7335. Berlin: Springer-Verlag. p. 103–118. ISBN 978-3-642-31137-6