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Flexible and Generalized Uncertainty Optimization = Theory and Approaches /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Flexible and Generalized Uncertainty Optimization/ by Weldon A. Lodwick, Luiz L. Salles-Neto.
Reminder of title:	Theory and Approaches /
Author:	Lodwick, Weldon A.
other author:	Salles-Neto, Luiz L.
Description:	IX, 193 p. 34 illus., 30 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-61180-4
ISBN:	9783030611804

Flexible and Generalized Uncertainty Optimization = Theory and Approaches /
Lodwick, Weldon A.

Flexible and Generalized Uncertainty OptimizationTheory and Approaches /[electronic resource] :by Weldon A. Lodwick, Luiz L. Salles-Neto. - 2nd ed. 2021. - IX, 193 p. 34 illus., 30 illus. in color.online resource. - Studies in Computational Intelligence,6961860-9503 ;. - Studies in Computational Intelligence,564.

An Introduction to Generalized Uncertainty Optimization -- Generalized Uncertainty Theory: A Language for Information Deficiency -- The Construction of Flexible and Generalized Uncertainty Optimization Input Data -- An Overview of Flexible and Generalized Uncertainty Optimization -- Flexible Optimization -- Generalized Uncertainty Optimization -- References. .

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.

ISBN: 9783030611804

Standard No.: 10.1007/978-3-030-61180-4doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Flexible and Generalized Uncertainty Optimization = Theory and Approaches /
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