QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming

Mattias Fält; Pontus Giselsson

doi:10.1109/CDC40024.2019.9029900

QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

Abstract

We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative refinement can be used to achieve good accuracy and to solve both types of sub-problems that arise from semi-definite problems.

Original language	English
Title of host publication	2019 IEEE Conference on Decision and Control (CDC)
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	4891-4897
Number of pages	7
ISBN (Electronic)	978-1-7281-1398-2
ISBN (Print)	978-1-7281-1399-9
DOIs	https://doi.org/10.1109/CDC40024.2019.9029900
Publication status	Published - 2019 Dec 11
Event	58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France Duration: 2019 Dec 11 → 2019 Dec 13

Conference

Conference	58th IEEE Conference on Decision and Control, CDC 2019
Country/Territory	France
City	Nice
Period	2019/12/11 → 2019/12/13

Subject classification (UKÄ)

Control Engineering

Access to Document

10.1109/CDC40024.2019.9029900

https://arxiv.org/abs/1911.12662

Cite this

@inproceedings{6d90c77aba3640bebd376a0d16832a23,

title = "QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming",

abstract = "We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative refinement can be used to achieve good accuracy and to solve both types of sub-problems that arise from semi-definite problems.",

author = "Mattias F{\"a}lt and Pontus Giselsson",

year = "2019",

month = dec,

day = "11",

doi = "10.1109/CDC40024.2019.9029900",

language = "English",

isbn = "978-1-7281-1399-9",

pages = "4891--4897",

booktitle = "2019 IEEE Conference on Decision and Control (CDC)",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "58th IEEE Conference on Decision and Control, CDC 2019 ; Conference date: 11-12-2019 Through 13-12-2019",

}

TY - GEN

T1 - QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming

AU - Fält, Mattias

AU - Giselsson, Pontus

PY - 2019/12/11

Y1 - 2019/12/11

N2 - We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative refinement can be used to achieve good accuracy and to solve both types of sub-problems that arise from semi-definite problems.

AB - We present a method for solving the general mixed constrained convex quadratic programming problem using an active set method on the dual problem. The approach is similar to existing active set methods, but we present a new way of solving the linear systems arising in the algorithm. There are two main contributions; we present a new way of factorizing the linear systems, and show how iterative refinement can be used to achieve good accuracy and to solve both types of sub-problems that arise from semi-definite problems.

UR - https://www.scopus.com/pages/publications/85082491507

U2 - 10.1109/CDC40024.2019.9029900

DO - 10.1109/CDC40024.2019.9029900

M3 - Paper in conference proceeding

SN - 978-1-7281-1399-9

SP - 4891

EP - 4897

BT - 2019 IEEE Conference on Decision and Control (CDC)

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 58th IEEE Conference on Decision and Control, CDC 2019

Y2 - 11 December 2019 through 13 December 2019

ER -

QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming

Abstract

Conference

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

Convergence Analysis and Improvements for Projection Algorithms and Splitting Methods

Large-Scale Optimization

Cite this

QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming

Abstract

Conference

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

Research output

Convergence Analysis and Improvements for Projection Algorithms and Splitting Methods

Projects

Large-Scale Optimization

Cite this