Open AccessA new iterative method for generalized equilibrium and constrained convex minimization problems
Author(s) -
M. Yazdi
Publication year - 2020
Publication title -
annales universitatis mariae curie-skłodowska. sectio a, mathematica
Language(s) - English
Resource type - Journals
eISSN - 2083-7402
pISSN - 0365-1029
DOI - 10.17951/a.2020.74.2.81-99
Subject(s) - minification , mathematical optimization , regular polygon , mathematics , convergence (economics) , convex optimization , projection (relational algebra) , iterative method , scheme (mathematics) , algorithm , mathematical analysis , geometry , economics , economic growth
The gradient-projection algorithm (GPA) plays an important role in solving constrained convex minimization problems. In this paper, we combine the GPA and averaged mapping approach to propose an explicit composite iterative scheme for finding a common solution of a generalized equilibrium problem and a constrained convex minimization problem. Then, we prove a strong convergence theorem which improves and extends some recent results.