Continuous GRASP with a local active-set method for bound-constrained global optimization
E. G. Birgin,  E. M. Gozzi, M. G. C. Resende, and R. M. A. Silva

To appear in J. of Global Optimization,  2010.

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.
 
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