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A Python/C library for bound-constrained global optimization with continuous GRASP

Ricardo M.A. Silva(ricardo.mabreu***at***gmail.com)
Mauricio G.C. Resende(mgcr***at***research.att.com)
Panos M. Pardalos(pardalos***at***ufl.edu)
Michael J. Hirsch(mjh8787***at***ufl.edu)

Abstract: This paper describes libcgrpp, a GNU-style dynamic shared Python/C library of the continuous greedy randomized adaptive search procedure (C-GRASP) for bound constrained global optimization. C-GRASP is an extension of the GRASP metaheuristic (Feo and Resende, 1989). After a brief introduction to C-GRASP, we show how to download, install, configure, and use the library through an illustrative example.

Keywords: GRASP, continuous GRASP, Global optimization, multimodal func- tions, continuous optimization, heuristic, stochastic algorithm, stochastic local search, nonlinear programming.

Category 1: Global Optimization

Category 2: Global Optimization (Stochastic Approaches )

Category 3: Optimization Software and Modeling Systems

Citation: AT&T Labs Research Technical Report, Florham Park, NJ 07932, July 2011.

Download: [PDF]

Entry Submitted: 08/08/2011
Entry Accepted: 08/08/2011
Entry Last Modified: 08/08/2011

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