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Flexible and Generalized Uncertainty Optimization

Theory and Approaches

Weldon A Lodwick, Luiz L Salles-Neto
Livre broché | Anglais | Studies in Computational Intelligence | n° 696
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Description

This book presents the theory and methods of flexible and generalized uncertainty optimization. Particularly, it describes the theory of generalized uncertainty in the context of optimization modeling. The book starts with an overview of flexible and generalized uncertainty optimization. It covers uncertainties that are both associated with lack of information and are more general than stochastic theory, where well-defined distributions are assumed. Starting from families of distributions that are enclosed by upper and lower functions, the book presents construction methods for obtaining flexible and generalized uncertainty input data that can be used in a flexible and generalized uncertainty optimization model. It then describes the development of the associated optimization model in detail. Written for graduate students and professionals in the broad field of optimization and operations research, this second edition has been revised and extended to include more worked examples and a section on interval multi-objective mini-max regret theory along with its solution method.

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Editeur:

Contenu

Nombre de pages :
193
Langue:
Anglais
Collection :
Tome:
n° 696

Caractéristiques

EAN:
9783030611828
Date de parution :
13-01-22
Format:
Livre broché
Format numérique:
Trade paperback (VS)
Dimensions :
156 mm x 234 mm
Poids :
290 g

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