The inexact fixed matrix iteration for solving large linear inequalities in a least squares sense

DOI10.1007/s11075-014-9892-2zbMath1322.65068OpenAlexW2007925361WikidataQ112879557 ScholiaQ112879557MaRDI QIDQ2346285

Yuan Lei

Publication date: 1 June 2015

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11075-014-9892-2

zbMATH Keywords

Krylov subspace methodlinear inequalitiesinconsistent systemsfixed matrix iterationinexact fixed matrix iterationleast squares QR method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Linear programming (90C05)

Related Items (4)

Best approximate solutions of inconsistent linear inequality systems ⋮ Continuous and discrete zeroing dynamics models using JMP function array and design formula for solving time-varying Sylvester-transpose matrix inequality ⋮ Hybrid algorithms with active set prediction for solving linear inequalities in a least squares sense ⋮ Continuous and discrete zeroing neural dynamics handling future unknown-transpose matrix inequality as well as scalar inequality of linear class

Uses Software

• LSQR
• MatrixMarket
• SuiteSparseQR
• SuitSparseQR
• symrcm
• CRAIG

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