Shrinking Projection Methods for Accelerating Relaxed Inertial Tseng-Type Algorithm with Applications
Hasanen A. Hammad, Habib ur Rehman, Manuel De la Sen
Abstract
Our main goal in this manuscript is to accelerate the relaxed inertial Tseng-type (RITT) algorithm by adding a shrinking projection (SP) term to the algorithm. Hence, strong convergence results were obtained in a real Hilbert space (RHS). A novel structure was used to solve an inclusion and a minimization problem under proper hypotheses. Finally, numerical experiments to elucidate the applications, performance, quickness, and effectiveness of our procedure are discussed.
Topics & Concepts
Convergence (economics)Inertial frame of referenceProjection (relational algebra)Hilbert spaceAlgorithmProjection methodMinificationType (biology)MathematicsTerm (time)Computer scienceSpace (punctuation)Mathematical optimizationDykstra's projection algorithmMathematical analysisPhysicsOperating systemBiologyEconomic growthEcologyQuantum mechanicsEconomicsAdvanced Optimization Algorithms ResearchOptimization and Variational AnalysisMatrix Theory and Algorithms