QPSchur: A dual, active-set, Schur-complement method for large-scale and structured convex quadratic programming

DOI10.1007/s11081-006-6588-zzbMath1167.90615OpenAlexW2034466934MaRDI QIDQ833407

Roscoe A. Bartlett, Lorenz T. Biegler

Publication date: 12 August 2009

Published in: Optimization and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11081-006-6588-z

zbMATH Keywords

quadratic programmingSchur complementdual spaceobject oriented programmingactive-set

Mathematics Subject Classification ID

Quadratic programming (90C20)

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Recent advances in quadratic programming algorithms for nonlinear model predictive control, Primal and dual active-set methods for convex quadratic programming, A factorization with update procedures for a KKT matrix arising in direct optimal control, Optimal sensitivity based on IPOPT, qpOASES: a parametric active-set algorithm for~quadratic programming, Complexity and convergence certification of a block principal pivoting method for box-constrained quadratic programs, Parameter optimization using the \(L_\infty \) exact penalty function and strictly convex quadratic programming problems, A dual gradient-projection method for large-scale strictly convex quadratic problems, Dual support method for solving convex quadratic programs, QPSchur, Globally Convergent Primal-Dual Active-Set Methods with Inexact Subproblem Solves, An Active-Set Method for Quadratic Programming Based On Sequential Hot-Starts, An exterior point polynomial-time algorithm for convex quadratic programming, Methods for convex and general quadratic programming

Uses Software

• rSQP++
• LOQO
• QPOPT
• ZQPCVX

Cites Work

• A numerically stable dual method for solving strictly convex quadratic programs
• What are Schur complements, anyway?
• Representations of quasi-Newton matrices and their use in limited memory methods
• A sparse nonlinear optimization algorithm
• Numerical Optimization
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