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A Linear Approximation Approach to Duality in Nonlinear Programming

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dc.creator Magnanti, Thomas L.
dc.date 2004-05-28T19:34:47Z
dc.date 2004-05-28T19:34:47Z
dc.date 1973-04
dc.date.accessioned 2013-10-09T02:39:13Z
dc.date.available 2013-10-09T02:39:13Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/5344
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description Linear approximation and linear programming duality theory are used as unifying tools to develop saddlepoint, Fenchel and local duality theory. Among results presented is a new and elementary proof of the necessity and sufficiency of the stability condition for saddlepoint duality, an equivalence between the saddlepoint and Fenchel theories, and nasc for an optimal solution of an optimization problem to be a Kuhn-Tucker point. Several of the classic "constraint qualifications" are discussed with respect to this last condition. In addition, generalized versions of Fenchel and Rockafeller duals are introduced. Finally, a shortened proof is given of a result of Mangasarian and Fromowitz that under fairly general conditions an optimal point is also a Fritz John point.
dc.description Supported in part by the US Army Research Office (Durham) under Contract DAHC04-70-C-0058
dc.format 1746 bytes
dc.format 1819696 bytes
dc.format application/pdf
dc.language en_US
dc.publisher Massachusetts Institute of Technology, Operations Research Center
dc.relation Operations Research Center Working Paper;OR 016-73
dc.title A Linear Approximation Approach to Duality in Nonlinear Programming
dc.type Working Paper


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