Rapid gradient penalty schemes and convergence for solving constrained convex optimization problem in Hilbert spaces

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Keywords:

Rapid gradient penalty algorithm, penalization, constraint minimization, fenchel conjugate

Abstract

The purposes of this paper are to establish and study the convergence of a new gradient scheme with penalization terms called rapid gradient penalty algorithm (RGPA) for minimizing a convex differentiable function over the set of minimizers of a convex differentiable constrained function. Under the observation of some appropriate choices for the available properties of the considered functions and scalars, we can generate a suitable algorithm that weakly converges to a minimal solution of the considered constraint minimization problem. Further, we also provide a numerical example to compare the rapid gradient penalty algorithm (RGPA) and the algorithm introduced by Peypouquet [20].

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Published

2021-10-13

How to Cite

Natthaphon Artsawang, & Kasamsuk Ungchittrakool. (2021). Rapid gradient penalty schemes and convergence for solving constrained convex optimization problem in Hilbert spaces. Journal of Computational Analysis and Applications (JoCAAA), 29(5), 910–921. Retrieved from http://eudoxuspress.com/index.php/pub/article/view/202

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