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A decomposition method for large scale MILPs, with performance guarantees and a power system application

Abstract:

All rights reserved. Lagrangian duality in mixed integer optimization is a useful framework for problem decomposition and for producing tight lower bounds to the optimal objective. However, in contrast to the convex case, it is generally unable to produce optimal solutions directly. In fact, solutions recovered from the dual may not only be suboptimal, but even infeasible. In this paper we concentrate on large scale mixed-integer programs with a specific structure that appears in a variety of...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
  • (Author's original, pdf, 437.3KB)
Publisher copy:
10.1016/j.automatica.2016.01.006

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
Elsevier
Journal:
Automatica More from this journal
Volume:
67
Pages:
144-156
Publication date:
2016-02-05
Acceptance date:
2015-12-07
DOI:
ISSN:
0005-1098
Keywords:
Pubs id:
pubs:612090
UUID:
uuid:2316ae82-f3bc-4991-ba7e-a4b8ffca66ea
Local pid:
pubs:612090
Source identifiers:
612090
Deposit date:
2016-05-25

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