Flexible and generalized uncertainty optimization [electronic resource] : theory and approaches / Weldon A. Lodwick, Luiz L. Salles-Neto.

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Flexible and generalized uncertainty optimization [electronic resource] : theory and approaches / Weldon A. Lodwick, Luiz L. Salles-Neto.

Second edition.

9783030611804 (electronic book)
3030611809 (electronic book)
9783030611798
3030611795

Cham, Switzerland : Springer, [2021]

English

1 online resource (ix, 193 pages) : illustrations (some color).

10.1007/978-3-030-61180-4 doi

QA402.5

519.6

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.

Includes bibliographical references.

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Online resource; title from PDF title page (SpringerLink, viewed March 3, 2021).

Studies in computational intelligence ; v. 696.

Print version: 9783030611798

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