A weighted least squares study of robustness in interior point linear programming
type: Item
instance of: scholarly article
title: A weighted least squares study of robustness in interior point linear programming
zbMATH Open document ID: 0799.90081
DOI: 10.1007/BF01299141
author: Alexander L. Hipolito
published in: Computational Optimization and Applications
publication date: 1993-08-30T00:00:00Z
review text: Although global convergence of the affine scaling algorithm has been proved, it is known that, for a bad choice of the initial interior point, the convergence may become very slow, or even numerical stall may occur. The paper in question studied the robustness of interior point linear programming algorithms, with respect to initial iterates that are close to the boundary (bad initial point). The author computes a modified Newton centering direction and shows that the approach which uses this direction is more robust than both the pure affine scaling approach and one which uses the Newton direction as the centering direction.
Mathematics Subject Classification ID: 90C05
Mathematics Subject Classification ID: 90-08
zbMATH DE Number: 370411
zbMATH Keywords: robustness of interior point linear programming algorithms
zbMATH Keywords: modified Newton centering direction
MaRDI profile type: Publication
cites work: An implementation of Karmarkar's algorithm for linear programming
cites work: A variation on Karmarkar’s algorithm for solving linear programming problems
cites work: Q5588268
cites work: Q3359644
cites work: Search directions for interior linear-programming methods
cites work: Degeneracy in interior point methods for linear programming: A survey
cites work: A survey of search directions in interior point methods for linear programming
cites work: A new polynomial-time algorithm for linear programming
cites work: Computational results of an interior point algorithm for large scale linear programming
cites work: Q4879581
cites work: Computational experience with a primal-dual interior point method for linear programming
cites work: Boundary Behavior of Interior Point Algorithms in Linear Programming
cites work: Computational experience with a dual affine variant of Karmarkar's method for linear programming
cites work: A simplified global convergence proof of the affine scaling algorithm
cites work: A modification of Karmarkar's linear programming algorithm
description: scientific article; zbMATH DE number 370411