The prox-Tikhonov regularization method for the proximal point algorithm in Banach spaces

Authors:
D. R. Sahu;J. C. Yao
Affiliations:
Department of Mathematics, Banaras Hindu University, Varanasi, India 221005;Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan 804
Venue:
Journal of Global Optimization
Year:
2011

Citing 5
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Abstract

It is known, by Rockafellar (SIAM J Control Optim 14:877---898, 1976), that the proximal point algorithm (PPA) converges weakly to a zero of a maximal monotone operator in a Hilbert space, but it fails to converge strongly. Lehdili and Moudafi (Optimization 37:239---252, 1996) introduced the new prox-Tikhonov regularization method for PPA to generate a strongly convergent sequence and established a convergence property for it by using the technique of variational distance in the same space setting. In this paper, the prox-Tikhonov regularization method for the proximal point algorithm of finding a zero for an accretive operator in the framework of Banach space is proposed. Conditions which guarantee the strong convergence of this algorithm to a particular element of the solution set is provided. An inexact variant of this method with error sequence is also discussed.