Quadrex Algorithm for Negative Definite Quadratic Programming Models

Arcillas, Mark Ivan P. and Castillano, Elmer C. (2022) Quadrex Algorithm for Negative Definite Quadratic Programming Models. Journal of Advances in Mathematics and Computer Science, 37 (6). pp. 57-65. ISSN 2456-9968

[thumbnail of 1647-Article Text-3207-2-10-20221012.pdf]

Text
1647-Article Text-3207-2-10-20221012.pdf - Published Version
Download (643kB)

Official URL: https://doi.org/10.9734/jamcs/2022/v37i630461

Abstract

In this paper, a quadrex algorithm for quadratic programming problems is introduced (n = 2) under linear and quadratic constraints. The quadrex algorithm considers on the behavior of the quadratic function near the origin or a translate of the origin, performs a series of translations
and orthogonal rotations to obtain the optimal solution of the objective function as well as taking considerations on the constraints of the problem. The method works provided that the eigenvalues of the matrix on quadratic form of the objective function is strictly negative, that is,
Q is negative-definite. The quadrex algorithm is a parallel counterpart of the simplex algorithm for linear programming models.

Item Type:	Article
Subjects:	Library Eprints > Mathematical Science
Depositing User:	Managing Editor
Date Deposited:	17 Feb 2023 06:45
Last Modified:	19 Jul 2024 05:22
URI:	http://news.pacificarchive.com/id/eprint/1370

Actions (login required)

: View Item