QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming
(2019) 58th IEEE Conference on Decision and Control, CDC 2019 p.4891-4897- 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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/6d90c77a-ba36-40be-bd37-6a0d16832a23
- author
- Fält, Mattias LU and Giselsson, Pontus LU
- organization
- publishing date
- 2019-12-11
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2019 IEEE Conference on Decision and Control (CDC)
- pages
- 7 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 58th IEEE Conference on Decision and Control, CDC 2019
- conference location
- Nice, France
- conference dates
- 2019-12-11 - 2019-12-13
- external identifiers
-
- scopus:85082491507
- ISBN
- 978-1-7281-1398-2
- 978-1-7281-1399-9
- DOI
- 10.1109/CDC40024.2019.9029900
- project
- Large-Scale Optimization
- language
- English
- LU publication?
- yes
- id
- 6d90c77a-ba36-40be-bd37-6a0d16832a23
- alternative location
- https://arxiv.org/abs/1911.12662
- date added to LUP
- 2020-03-09 14:53:06
- date last changed
- 2024-05-01 07:42:33
@inproceedings{6d90c77a-ba36-40be-bd37-6a0d16832a23, 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 = {{Fält, Mattias and Giselsson, Pontus}}, booktitle = {{2019 IEEE Conference on Decision and Control (CDC)}}, isbn = {{978-1-7281-1398-2}}, language = {{eng}}, month = {{12}}, pages = {{4891--4897}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{QPDAS: Dual Active Set Solver for Mixed Constraint Quadratic Programming}}, url = {{http://dx.doi.org/10.1109/CDC40024.2019.9029900}}, doi = {{10.1109/CDC40024.2019.9029900}}, year = {{2019}}, }