GENERALIZED RELAXED PROXIMAL POINT ALGORITHMS INVOLVING RELATIVE MAXIMAL ACCRETIVE MODELS WITH APPLICATIONS IN BANACH SPACES

- Journal title : Communications of the Korean Mathematical Society
- Volume 25, Issue 2, 2010, pp.313-325
- Publisher : The Korean Mathematical Society
- DOI : 10.4134/CKMS.2010.25.2.313

Title & Authors

GENERALIZED RELAXED PROXIMAL POINT ALGORITHMS INVOLVING RELATIVE MAXIMAL ACCRETIVE MODELS WITH APPLICATIONS IN BANACH SPACES

Verma, Ram U.;

Verma, Ram U.;

Abstract

General models for the relaxed proximal point algorithm using the notion of relative maximal accretiveness (RMA) are developed, and then the convergence analysis for these models in the context of solving a general class of nonlinear inclusion problems differs significantly than that of Rockafellar (1976), where the local Lipschitz continuity at zero is adopted instead. Moreover, our approach not only generalizes convergence results to real Banach space settings, but also provides a suitable alternative to other problems arising from other related fields.

Keywords

variational inclusions;maximal relaxed accretive mapping;relative maximal accretive mapping;generalized resolvent operator;

Language

English

Cited by

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