Statements (51)
Predicate | Object |
---|---|
gptkbp:instanceOf |
gptkb:mathematical_concept
|
gptkbp:appliesTo |
linear programming
nonlinear programming convex optimization |
gptkbp:field |
mathematical optimization
|
gptkbp:hasApplication |
gptkb:signal_processing
combinatorial optimization control theory game theory resource allocation statistical estimation support vector machines energy minimization data fitting network flow production planning assignment problem integer programming network design multi-objective optimization quadratic programming robust optimization semidefinite programming stochastic programming portfolio optimization resource scheduling transportation problem facility location |
gptkbp:hasProperty |
dual problem provides lower bound for minimization
dual problem provides upper bound for maximization every optimization problem has a dual problem strong duality holds under certain conditions weak duality always holds |
https://www.w3.org/2000/01/rdf-schema#label |
Duality (optimization)
|
gptkbp:notable_for |
gptkb:Karush-Kuhn-Tucker_conditions
gptkb:Farkas'_lemma gptkb:Fenchel_duality gptkb:Slater's_condition Lagrange duality |
gptkbp:relatedConcept |
gptkb:Lagrangian_duality
dual problem strong duality duality gap primal problem weak duality |
gptkbp:usedIn |
gptkb:machine_learning
economics engineering operations research |
gptkbp:bfsParent |
gptkb:Integer_Linear_Programming
|
gptkbp:bfsLayer |
8
|