Linear programming with nonparametric penalty programs and iterated thresholding

It is known  [Mangasarian, A Newton method for linear programming, J. Optim. Theory Appl. 121 (2004), pp. 1-18] that every linear program can be solved exactly by minimizing an unconstrained quadratic penalty program. The penalty program is parameterized by a scalar t>0, and one is able to solve...

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Bibliographic Details

Published in:	Optimization methods & software Vol. 38; no. 1; pp. 107 - 127
Main Authors:	Kline, Jeffery, Fung, Glenn Martin
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 02.01.2023 Taylor & Francis Ltd
Subjects:	Algorithms duality fixed point Iterative methods Linear programming Newton methods nonexpansive map Nonparametric statistics Parameterization penalty method Quadratic programming
ISSN:	1055-6788, 1029-4937
Online Access:	Get full text
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