Hybrid Algorithms for Minimization Problems over the Solutions of Generalized Mixed Equilibrium and Variational Inclusion Problems
Copyright policy )Hybrid Algorithms for Minimization Problems over the Solutions of Generalized Mixed Equilibrium and Variational Inclusion Problems
We introduce a new general hybrid iterative algorithm for finding a common element of the set of solution of fixed point for a nonexpansive mapping, the set of solution of generalized mixed equilibrium problem, and the set of solution of the variational inclusion for a β‐inverse‐strongly monotone mapping in a real Hilbert space. We prove that the sequence converges strongly to a common element of the above three sets under some mild conditions. Our results improve and extend the corresponding results of Marino and Xu (2006), Yao and Liou (2010), Tan and Chang (2011), and other authors.
Economics, FOS: Political science, Fixed-Point Problems, Multi-Objective Transportation Problem Optimization, Engineering, Interior-Point Methods, Nonexpansive Mappings, Political science, Numerical methods for variational inequalities and related problems, Variational inequality, Numerical Analysis, Numerical Optimization Techniques, Minification, Mathematical optimization, Hilbert space, Iterative Algorithms for Nonlinear Operators and Optimization, Programming language, Algorithm, Solution set, Computational Theory and Mathematics, Physical Sciences, Convergence (economics), Element (criminal law), Geometry, Set (abstract data type), FOS: Law, Space (punctuation), Fixed-point theorems, FOS: Mathematics, Genetics, Iterative Algorithms, Biology, Economic growth, Pure mathematics, Applied mathematics, Computer science, Operating system, Control and Systems Engineering, Strongly monotone, FOS: Biological sciences, Computer Science, Monotone polygon, Contraction-type mappings, nonexpansive mappings, \(A\)-proper mappings, etc., Inverse, Law, Mathematics, Mixed-Integer Nonlinear Programs, Sequence (biology)
Economics, FOS: Political science, Fixed-Point Problems, Multi-Objective Transportation Problem Optimization, Engineering, Interior-Point Methods, Nonexpansive Mappings, Political science, Numerical methods for variational inequalities and related problems, Variational inequality, Numerical Analysis, Numerical Optimization Techniques, Minification, Mathematical optimization, Hilbert space, Iterative Algorithms for Nonlinear Operators and Optimization, Programming language, Algorithm, Solution set, Computational Theory and Mathematics, Physical Sciences, Convergence (economics), Element (criminal law), Geometry, Set (abstract data type), FOS: Law, Space (punctuation), Fixed-point theorems, FOS: Mathematics, Genetics, Iterative Algorithms, Biology, Economic growth, Pure mathematics, Applied mathematics, Computer science, Operating system, Control and Systems Engineering, Strongly monotone, FOS: Biological sciences, Computer Science, Monotone polygon, Contraction-type mappings, nonexpansive mappings, \(A\)-proper mappings, etc., Inverse, Law, Mathematics, Mixed-Integer Nonlinear Programs, Sequence (biology)
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