Weak convergence of explicit extragradient algorithms for solving equilibirum problems

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초록

This paper aims to propose two new algorithms that are developed by implementing inertial and subgradient techniques to solve the problem of pseudomonotone equilibrium problems. The weak convergence of these algorithms is well established based on standard assumptions of a cost bi-function. The advantage of these algorithms was that they did not need a line search procedure or any information on Lipschitz-type bifunction constants for step-size evaluation. A practical explanation for this is that they use a sequence of step-sizes that are updated at each iteration based on some previous iterations. For numerical examples, we discuss two well-known equilibrium models that assist our well-established convergence results, and we see that the suggested algorithm has a competitive advantage over time of execution and the number of iterations.

키워드

Equilibrium problemExtragradient methodLipschitz-type conditionsNash-Cournot equilibrium model of electricity marketsAUXILIARY PROBLEM PRINCIPLEINERTIAL PROXIMAL METHODVARIATIONAL-INEQUALITIESMONOTONE-OPERATORSEQUILIBRIUMPROJECTION
제목
Weak convergence of explicit extragradient algorithms for solving equilibirum problems
저자
Rehman, Habib UrKumam, PoomCho, Yeol JeYordsorn, Pasakorn
DOI
10.1186/s13660-019-2233-1
발행일
2019-12
유형
Article
저널명
Journal of Inequalities and Applications
2019
1