Continuous GRASP with a local active-set method for bound-constrained global optimization
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
20/10/2012
20/10/2012
2010
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Resumo |
Global optimization seeks a minimum or maximum of a multimodal function over a discrete or continuous domain. In this paper, we propose a hybrid heuristic-based on the CGRASP and GENCAN methods-for finding approximate solutions for continuous global optimization problems subject to box constraints. Experimental results illustrate the relative effectiveness of CGRASP-GENCAN on a set of benchmark multimodal test functions. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Brazil Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) |
Identificador |
JOURNAL OF GLOBAL OPTIMIZATION, v.48, n.2, p.289-310, 2010 0925-5001 http://producao.usp.br/handle/BDPI/30363 10.1007/s10898-009-9494-z |
Idioma(s) |
eng |
Publicador |
SPRINGER |
Relação |
Journal of Global Optimization |
Direitos |
restrictedAccess Copyright SPRINGER |
Palavras-Chave | #Global optimization #Stochastic methods #Active-set methods #Heuristic #CGRASP #GENCAN #AUGMENTED LAGRANGIAN-METHODS #ALGORITHM #Operations Research & Management Science #Mathematics, Applied |
Tipo |
article original article publishedVersion |