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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Flexible and Generalized Uncertainty Optimization: Theory and Approaches

Flexible and Generalized Uncertainty Optimization: Theory and Approaches

Lodwick, Weldon A.
Salles-Neto, Luiz L.

Hardcover

Series: Studies in Computational Intelligence, Book 696

Business GeneralTechnology & EngineeringGeneral Mathematics

ISBN10: 3030611795
ISBN13: 9783030611798
Publisher: Springer Nature
Published: Jan 13 2021
Pages: 193
Weight: 1.02
Height: 0.50 Width: 6.14 Depth: 9.21
Language: English

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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