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Lagrangian relaxati...
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Kiwiel, Krzysztof C.Systems Research Institute, Warszawa
(author)
Lagrangian relaxation via ballstep subgradient methods
- Article/chapterEnglish2007
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Institute for Operations Research and the Management Sciences (INFORMS),2007
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LIBRIS-ID:oai:DiVA.org:liu-40001
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https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-40001URI
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https://doi.org/10.1287/moor.1070.0261DOI
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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We exhibit useful properties of ballstep subgradient methods for convex optimization using level controls for estimating the optimal value. Augmented with simple averaging schemes, they asymptotically find objective and constraint subgradients involved in optimality conditions. When applied to Lagrangian relaxation of convex programs, they find both primal and dual solutions, and have practicable stopping criteria. Up until now, similar results have only been known for proximal bundle methods, and for subgradient methods with divergent series stepsizes, whose convergence can be slow. Encouraging numerical results are presented for large-scale nonlinear multicommodity network flow problems. ©2007 INFORMS.
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Larsson, Torbjörn,1957-Linköpings universitet,Tekniska högskolan,Optimeringslära(Swepub:liu)torla64
(author)
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Lindberg, Per Olov,1942-Linköpings universitet,Tekniska högskolan,Optimeringslära(Swepub:liu)perli67
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Systems Research Institute, WarszawaTekniska högskolan
(creator_code:org_t)
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In:Mathematics of Operations Research: Institute for Operations Research and the Management Sciences (INFORMS)32:3, s. 669-6860364-765X1526-5471
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