Modified Projection Method for General Strongly Monotone Variational Inequalities
LV Yu-hua
Abstract
LV Yu-hua
Abstract
A modified projection method for solving general strongly monotone variational inequalities is presented.A practical and robust stepsize choice strategy,termed self-adaptive procedure,is developed.The algorithm is global convergent for strongly monotone operator.Numerical results and comparison with some existing projection-type methods are given to illustrate the efficiency of the proposed method.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
A modified projection method for solving general strongly monotone variational inequalities is presented.A practical and robust stepsize choice strategy,termed self-adaptive procedure,is developed.The algorithm is global convergent for strongly monotone operator.Numerical results and comparison with some existing projection-type methods are given to illustrate the efficiency of the proposed method.
Key concepts: Variational inequality, Monotone polygon, Projection (relational algebra), Mathematics, Projection method, Applied mathematics, Mathematical optimization, Operator (biology)