Convergence of Halpern’s Iteration Method with Applications in Optimization
Huiqiang Qi, Hong‐Kun Xu
Abstract
Halpern’s iteration method, discovered by Halpern in 1967, is an iterative algorithm for finding fixed points of a nonexpansive mapping in Hilbert and Banach spaces. Since many optimization problems can be cast into fixed point problems of nonexpansive mappings, Halpern’s method plays an important role in optimization methods. This paper discusses recent advances in convergence and rate of convergence results of Halpern’s method, and applications in optimization problems, including variational inequalities, monotone inclusions, Douglas-Rachford splitting method, and minimax problems.
Topics & Concepts
MathematicsHilbert spaceVariational inequalityMonotone polygonFixed pointBanach spaceConvergence (economics)MinimaxApplied mathematicsIterative methodOptimization problemMathematical optimizationMathematical analysisGeometryEconomic growthEconomicsOptimization and Variational AnalysisAdvanced Optimization Algorithms ResearchFixed Point Theorems Analysis