Abstract

We consider the split feasibility problem (SFP) in Hilbert spaces, inspired by extragradient method presented by Ceng, Ansari for split feasibility problem, subgradient extragradient method proposed by Censor, and variant extragradient-type method presented by Yao for variational inequalities; we suggest an extragradient-type algorithm for the SFP. We prove the strong convergence under some suitable conditions in infinite-dimensional Hilbert spaces.

Highlights

  • The convex feasibility problem (CFP) is to find a common point in the intersection of finitely many convex sets

  • We consider the split feasibility problem (SFP) in Hilbert spaces, inspired by extragradient method presented by Ceng, Ansari for split feasibility problem, subgradient extragradient method proposed by Censor, and variant extragradient-type method presented by Yao for variational inequalities; we suggest an extragradient-type algorithm for the SFP

  • We prove the strong convergence under some suitable conditions in infinite-dimensional Hilbert spaces

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Summary

A New Extragradient-Type Algorithm for the Split Feasibility Problem

School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China We consider the split feasibility problem (SFP) in Hilbert spaces, inspired by extragradient method presented by Ceng, Ansari for split feasibility problem, subgradient extragradient method proposed by Censor, and variant extragradient-type method presented by Yao for variational inequalities; we suggest an extragradient-type algorithm for the SFP. We prove the strong convergence under some suitable conditions in infinite-dimensional Hilbert spaces.

Introduction
Preliminaries
Algorithm and Its Convergence Analysis
Conclusion
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