arrow
Return

Implementation of an interior point method with basis preconditioning

delete2020-02-24
delete6
delete
OA
AI
L
Lukas Schork *
J
Jacek Gondzio
DOI:10.1007/s12532-020-00181-8delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
The implementation of a linear programming interior point solver is described that is based on iterative linear algebra. The linear systems are preconditioned by a basis matrix, which is updated from one interior point iteration to the next to bound the entries in a certain tableau matrix. The update scheme is based on simplex-type pivot operations and is implemented using linear algebra techniques from the revised simplex method. An initial basis is constructed by a crash procedure after a few interior point iterations. The basis at the end of the interior point solve provides the starting basis for a crossover method which recovers a basic solution to the linear program. Results of a computational study on a diverse set of medium to large-scale problems are discussed.
Keywords:
Linear programming
Interior point methods
Basis preconditioning
Crossover
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Mathematical Programming Computation cover
Mathematical Programming Computation
IF:
3.6
Papers:
197
Citations:
1.9K

Organization

U
University of Edinburgh
Scholars:
5.2W
Papers: 4.6W
Citations: 71