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Kniha Multiple Criteria Optimization Xavier Gandibleux

Multiple Criteria Optimization

State of the Art Annotated Bibliographic Surveys

Autor: Xavier Gandibleux
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Springer-Verlag New York Inc.
Dostupnost: Skladem u dodavatele v malém množství
Odesíláme za 13-18 dnů
3 938 Kč
With the ever rapidly increasing rate of publications in the area and the development of subfields,...

Informace o knize

Autor
Xavier Gandibleux
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2013
Stránek
496
EAN
9781475776621
ISBN
1475776624
Enbook ID
02181742
Vydavatel
Springer-Verlag New York Inc.
Hmotnost
795
Rozměry
155 x 235 x 29

Kompletní popis

With the ever rapidly increasing rate of publications in the area and the development of subfields, these were mostly devoted to particular aspects of multicriteria optimization: Multiobjective Integer Programming, Multi-objective Combinatorial Optimization, Vector Optimization, Multiobjective Evolutionary Methods, Applications of MCDM, MCDM Software, Goal Programming. Hence the need for a comprehensive overview of the literature in multicriteria optimization that could serve as a state of the art survey and guide to the vast amount of publications. Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys is precisely this book. Experts in various areas of multicriteria optimization have contributed to the volume. The chapters in this book roughly follow a thread from most general to more specific. Some of them are about particular types of problems (Theory of Vector Optimization, Nonlinear Multiobjective Programming, Fuzzy Multiobjective Programming, Multiobjective Combinatorial Optimization, Multicriteria Scheduling Problems), while the others are focused on multi-objective methodologies (Goal Programming, Interactive Methods, Evolutionary Algorithms, Data Envelopment Analysis). All contributing authors invested great effort to produce comprehensive overviews and bibliographies and to have references that are as precise as possible. §

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