Hybrid Conjugate Gradient Method for a Convex Optimization Problem over the Fixed-Point Set of a Nonexpansive Mapping

H. Iiduka ()
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H. Iiduka: Tokyo Institute of Technology

Journal of Optimization Theory and Applications, 2009, vol. 140, issue 3, No 6, 463-475

Abstract: Abstract The main aim of the paper is to accelerate the existing method for a convex optimization problem over the fixed-point set of a nonexpansive mapping. To achieve this goal, we present an algorithm (Algorithm 3.1) by using the conjugate gradient direction. We present also a convergence analysis (Theorem 3.1) under some assumptions. Finally, to demonstrate the effectiveness and performance of the proposed method, we present numerical comparisons of the existing method with the proposed method.

Keywords: Convex optimization problems; Nonexpansive mappings; Fixed points; Conjugate gradient methods; Hybrid steepest descent methods (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s10957-008-9463-6

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