Strong Convergence of an Inexact Proximal Point Algorithm in a Banach Space

Behzad Djafari Rouhani () and Vahid Mohebbi ()
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Behzad Djafari Rouhani: University of Texas at El Paso
Vahid Mohebbi: University of Texas at El Paso

Journal of Optimization Theory and Applications, 2020, vol. 186, issue 1, No 7, 134-147

Abstract: Abstract By using our own approach, we study the strong convergence of an inexact proximal point algorithm with possible unbounded errors for a maximal monotone operator in a Banach space. We give a necessary and sufficient condition for the zero set of the operator to be nonempty and show that, in this case, this iterative sequence converges strongly to a zero of the operator. We present also some applications of our results to equilibrium problems and optimization. Our proximal point algorithm contains, as a special case, the one considered in Hilbert space by Djafari Rouhani and Moradi in (J Optim Theory Appl 172:222–235, 2017) and solves the open problem of extending it to a Banach space, which was stated in that paper and in Djafari Rouhani and Moradi in (J Optim Theory Appl 181:864–882, 2019) . Since the nonexpansiveness of the resolvent operator, which holds in Hilbert space, is not valid anymore in Banach space, our results require new methods of proofs, and significantly improve upon the previous results, both in theory and in applications.

Keywords: Equilibrium problems; Maximal monotone operator; Proximal point method; Resolvent; Strong convergence; 47H10; 47H05; 47J25 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10957-020-01695-w

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