Continuous GRASP with a local active-set method for bound-constrained global optimization
Ernesto G. Birgin (egbirginime.usp.br)
Abstract: 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.
Keywords: Global optimization, stochastic methods, active-set methods, heuristic, CGRASP, GENCAN
Category 1: Global Optimization
Category 2: Global Optimization (Stochastic Approaches )
Citation: AT&T Labs Research Technical Report, AT&T Labs Research, Shannon Laboratory, Florham Park, NJ 07932, April 2009.
Entry Submitted: 04/27/2009
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