AN ADAPTIVE GRADIENT ALGORITHM FOR LARGE-SCALE NONLINEAR BOUND CONSTRAINED OPTIMIZATION

Wanyou Cheng () and Erbao Cao ()
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Wanyou Cheng: College of Computer, Dongguan University of Technology, Dongguan 523000, China
Erbao Cao: College of Econometrics and Trade, Hunan University, Changsha 410082, China

Asia-Pacific Journal of Operational Research (APJOR), 2013, vol. 30, issue 03, 1-12

Abstract: In this paper, an adaptive gradient algorithm (AGM) for box constrained optimization is developed. The algorithm is based on an active set identification technique and consists of a nonmonotone gradient projection step, a conjugate gradient step and a rule for branching between the two steps. We show that the method is globally convergent under appropriate conditions. Numerical experiments are presented using bound constrained problems in the CUTEr test problem library.

Keywords: Bound constrained optimization; PRP method; global convergence (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S0217595913400058

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