A hyperbolic penalty method to solve structured convex minimization problems
| Author | Hamdi, A. |
| Author | Al-Maadeed, T.K. |
| Author | Taati, A. |
| Available date | 2023-09-24T07:55:32Z |
| Publication Date | 2020 |
| Publication Name | International Journal of Advanced and Applied Sciences |
| Resource | Scopus |
| Abstract | This paper presents a decomposition algorithm based on the smooth hyperbolic penalty, which leads to a scheme suitable for parallelized computations. The proposed algorithm can be seen as a separable version of the earlier hyperbolic penalty method built, and its main idea is related to a penalty-type scheme mixed with a kind of resource allocation approach to decompose large scale separable constrained minimization programs. 2020 The Authors. |
| Sponsor | This section is devoted to some numerical tests where we study the numerical behavior of the HDA. The study will tackle the feasibility, optimality, and stability of this method with respect to the parameters involved. Furthermore, an extension of the HDA, the Proximal Hyperbolic Decomposition Algorithm (PHDA), described below, is tested. This study is completed by a brief comparison involving HDA, PHDA, and the well-known strong CVX tool for some Convex Programming models developed by S.T. Boyd and M.C Grant from Standford University (Grant and Boyd, 2020). CVX is a Matlab-based modeling system for constructing and solving some convex programs (CPs). CVX supports a number of standard problem types, including linear and quadratic programs, and it is mainly based on primal-dual interior-point techniques. |
| Language | en |
| Publisher | Institute of Advanced Science Extension (IASE) |
| Subject | Convex functions Decomposition Hyperbolic penalty methods Large scale optimization |
| Type | Article |
| Pagination | 87-97 |
| Issue Number | 5 |
| Volume Number | 7 |
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