Vector Optimization with Infimum and Supremum [recurso electrónico] / by Andreas Löhne.
Tipo de material: TextoSeries Vector OptimizationEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Descripción: X, 206 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642183515Tema(s): Economics | Algebra | Algorithms | Mathematical optimization | Economics/Management Science | Operations Research/Decision Theory | Optimization | Order, Lattices, Ordered Algebraic Structures | Operations Research, Management Science | AlgorithmsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 658.40301 Clasificación LoC:HD30.23Recursos en línea: Libro electrónico En: Springer eBooksResumen: The theory of Vector Optimization is developed by a systematic usage of infimum and supremum. In order to get existence and appropriate properties of the infimum, the image space of the vector optimization problem is embedded into a larger space, which is a subset of the power set, in fact, the space of self-infimal sets. Based on this idea we establish solution concepts, existence and duality results and algorithms for the linear case. The main advantage of this approach is the high degree of analogy to corresponding results of Scalar Optimization. The concepts and results are used to explain and to improve practically relevant algorithms for linear vector optimization problems.Tipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | HD30.23 (Browse shelf(Abre debajo)) | 1 | No para préstamo | 375714-2001 |
The theory of Vector Optimization is developed by a systematic usage of infimum and supremum. In order to get existence and appropriate properties of the infimum, the image space of the vector optimization problem is embedded into a larger space, which is a subset of the power set, in fact, the space of self-infimal sets. Based on this idea we establish solution concepts, existence and duality results and algorithms for the linear case. The main advantage of this approach is the high degree of analogy to corresponding results of Scalar Optimization. The concepts and results are used to explain and to improve practically relevant algorithms for linear vector optimization problems.
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