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Flexible and generalized uncertainty...

Lodwick, Weldon A.

Flexible and generalized uncertainty optimizationtheory and approaches /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Flexible and generalized uncertainty optimizationby Weldon A. Lodwick, Luiz L. Salles-Neto.
其他題名:	theory and approaches /
作者:	Lodwick, Weldon A.
其他作者:	Salles-Neto, Luiz L.
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	ix, 193 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Mathematical optimization.
電子資源:	https://doi.org/10.1007/978-3-030-61180-4
ISBN:	9783030611804$q(electronic bk.)

Flexible and generalized uncertainty optimizationtheory and approaches /
Lodwick, Weldon A.

Flexible and generalized uncertainty optimizationtheory and approaches /[electronic resource] :by Weldon A. Lodwick, Luiz L. Salles-Neto. - Second edition. - Cham :Springer International Publishing :2021. - ix, 193 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6961860-949X ;. - Studies in computational intelligence ;v. 216..

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$q(electronic bk.)

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

183292
Mathematical optimization.

LC Class. No.: QA402.5 / .L639 2021

Dewey Class. No.: 519.6

Flexible and generalized uncertainty optimizationtheory and approaches /
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