dc.contributor.author |
Jeyakumar, V |
|
dc.contributor.author |
Srisatkunarajah, S |
|
dc.date.accessioned |
2014-02-01T09:31:21Z |
|
dc.date.accessioned |
2022-06-28T06:46:04Z |
|
dc.date.available |
2014-02-01T09:31:21Z |
|
dc.date.available |
2022-06-28T06:46:04Z |
|
dc.date.issued |
2009-02 |
|
dc.identifier.issn |
00223239 |
|
dc.identifier.uri |
http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/172 |
|
dc.description.abstract |
We present new conditions for a Karush-Kuhn-Tucker point to be a global minimizer of a mathematical programming problem which may have many local minimizers that are not global. The new conditions make use of underestimators of the Lagrangian at the Karush-Kuhn-Tucker point. We establish that a Karush-Kuhn-Tucker point is a global minimizer if the Lagrangian admits an underestimator, which is convex or, more generally, has the property that every stationary point is a global minimizer. In particular, we obtain sufficient conditions by using the fact that the biconjugate function of the Lagrangian is a convex underestimator at a point whenever it coincides with the Lagrangian at that point. We present also sufficient conditions for weak and strong duality results in terms of underestimators. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Springer Science+Business Media, LLC |
en_US |
dc.subject |
Biconjugate functions |
en_US |
dc.subject |
Karush-Kuhn-Tucker conditions |
en_US |
dc.subject |
Strong duality |
en_US |
dc.subject |
Sufficient optimality conditions |
en_US |
dc.subject |
Underestimators |
en_US |
dc.title |
New sufficiency for global optimality and duality of mathematical programming problems via underestimators |
en_US |
dc.type |
Article |
en_US |