Cartis, C. and Yan, Y. (2016) Active-set prediction for interior point methods using controlled perturbations. Computational Optimization and Applications, 63 (3). pp. 639-684. ISSN 0926-6003
Abstract
We propose the use of controlled perturbations to address the challenging question of optimal active-set prediction for interior point methods. Namely, in the context of linear programming, we consider perturbing the inequality constraints/bounds so as to enlarge the feasible set. We show that if the perturbations are chosen appropriately, the solution of the original problem lies on or close to the central path of the perturbed problem. We also find that a primal-dual path-following algorithm applied to the perturbed problem is able to accurately predict the optimal active set of the original problem when the duality gap for the perturbed problem is not too small; furthermore, depending on problem conditioning, this prediction can happen sooner than predicting the active set for the perturbed problem or when the original one is solved. Encouraging preliminary numerical experience is reported when comparing activity prediction for the perturbed and unperturbed problem formulations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Springer. This is an author produced version of a paper subsequently published in JOURNAL. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Mar 2016 15:41 |
Last Modified: | 19 Apr 2017 07:48 |
Published Version: | https://dx.doi.org/10.1007/s10589-015-9791-z |
Status: | Published |
Publisher: | Springer Verlag |
Refereed: | Yes |
Identification Number: | 10.1007/s10589-015-9791-z |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:96569 |