Continuous GRASP with a local active-set method for bound-constrained global optimization


Autoria(s): BIRGIN, Ernesto G.; GOZZI, Erico M.; RESENDE, Mauricio G. C.; SILVA, Ricardo M. A.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2010

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

http://dx.doi.org/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