Convex Relaxations for Mixed-Integer Nonlinear Programs - Couverture souple

Ballerstein, Martin

9783954044740: Convex Relaxations for Mixed-Integer Nonlinear Programs

Couverture souple

ISBN 10 : 3954044749 ISBN 13 : 9783954044740

Editeur : Cuvillier Verlag, 2013

Afficher les exemplaires de cette �dition comportant l'ISBN

0 D'occasion

5 Neuf

De EUR 43,85

D�tails de l'�dition

�diteur: Cuvillier Verlag
Date d'�dition: 2013
Langue: anglais
ISBN 10: 3954044749
ISBN 13: 9783954044740
Reliure: Broch�
Nombre de pages: 252
Coordonn�es du fabricant: non disponible
Personne responsable: non disponible

R�sultats de recherche pour Convex Relaxations for Mixed-Integer Nonlinear Programs

Image fournie par le vendeur

Convex Relaxations for Mixed-Integer Nonlinear Programs

Martin Ballerstein

Edit� par Cuvillier Sep 2013, 2013

ISBN 10 : 3954044749 ISBN 13 : 9783954044740

Neuf Taschenbuch

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis deals with new techniques to construct a strong convex relaxation for a mixed-integer nonlinear program (MINLP). While local optimization software can quickly identify promising operating points of MINLPs, the solution of the convex relaxation provides a global bound on the optimal value of the MINLP that can be used to evaluate the quality of the local solution. Certainly, the efficiency of this evaluation is strongly dependent on the quality of the convex relaxation. Convex relaxations of general MINLPs can be constructed by replacing each nonlinear function occurring in the model description by convex underestimating and concave overestimating functions. In this setting, it is desired to use the best possible convex underestimator and concave overestimator of a given function over an underlying domain � the so-called convex and concave envelope, respectively. However, the computation of these envelopes can be extremely difficult so that analytical expressions for envelopes are only available for some classes of well-structured functions. 252 pp. Englisch. N� de r�f. du vendeur 9783954044740

Contacter le vendeur

Acheter neuf

EUR 43,85

Exp�dition �EUR 23
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 2 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Convex Relaxations for Mixed-Integer Nonlinear Programs

Ballerstein, Martin

Edit� par Cuvillier Verlag, 2013

ISBN 10 : 3954044749 ISBN 13 : 9783954044740

Neuf Couverture souple

impression � la demande

Vendeur : moluna, Greven, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnThis thesis deals with new techniques to construct a strong convex relaxation for a mixed-integer nonlinear program (MINLP). While local optimization software can quickly identify promising operating points of MINLPs, the solution. N� de r�f. du vendeur 75054363

Contacter le vendeur

Acheter neuf

EUR 43,85

Exp�dition �EUR 48,99
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Convex Relaxations for Mixed-Integer Nonlinear Programs

Martin Ballerstein

Edit� par Cuvillier, Cuvillier Sep 2013, 2013

ISBN 10 : 3954044749 ISBN 13 : 9783954044740

Neuf Taschenbuch

impression � la demande

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This thesis deals with new techniques to construct a strong convex relaxation for a mixed-integer nonlinear program (MINLP). While local optimization software can quickly identify promising operating points of MINLPs, the solution of the convex relaxation provides a global bound on the optimal value of the MINLP that can be used to evaluate the quality of the local solution. Certainly, the efficiency of this evaluation is strongly dependent on the quality of the convex relaxation.Convex relaxations of general MINLPs can be constructed by replacing each nonlinear function occurring in the model description by convex underestimating and concave overestimating functions. In this setting, it is desired to use the best possible convex underestimator and concave overestimator of a given function over an underlying domain - the so-called convex and concave envelope, respectively. However, the computation of these envelopes can be extremely difficult so that analytical expressions for envelopes are only available for some classes of well-structured functions.Cuvillier Verlag, Nonnenstieg 8, 37075 G�ttingen 252 pp. Englisch. N� de r�f. du vendeur 9783954044740

Contacter le vendeur

Acheter neuf

EUR 43,85

Exp�dition �EUR 60
Exp�dition depuis Allemagne vers Etats-Unis

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Convex Relaxations for Mixed-Integer Nonlinear Programs

Martin Ballerstein

Edit� par Cuvillier

ISBN 10 : 3954044749 ISBN 13 : 9783954044740

Neuf Taschenbuch

impression � la demande

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This thesis deals with new techniques to construct a strong convex relaxation for a mixed-integer nonlinear program (MINLP). While local optimization software can quickly identify promising operating points of MINLPs, the solution of the convex relaxation provides a global bound on the optimal value of the MINLP that can be used to evaluate the quality of the local solution. Certainly, the efficiency of this evaluation is strongly dependent on the quality of the convex relaxation. Convex relaxations of general MINLPs can be constructed by replacing each nonlinear function occurring in the model description by convex underestimating and concave overestimating functions. In this setting, it is desired to use the best possible convex underestimator and concave overestimator of a given function over an underlying domain � the so-called convex and concave envelope, respectively. However, the computation of these envelopes can be extremely difficult so that analytical expressions for envelopes are only available for some classes of well-structured functions. N� de r�f. du vendeur 9783954044740

Contacter le vendeur