Flexible and generalized uncertainty optimization : theory and methods /

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Bibliographic Details
Author / Creator:Lodwick, Weldon A., author.
Imprint:Cham, Switzerland : Springer, 2017.
Description:1 online resource (x, 190 pages) : illustrations (some color)
Language:English
Series:Studies in computational intelligence, 1860-949X ; volume 696
Studies in computational intelligence ; v. 696.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11271123
Hidden Bibliographic Details
Other authors / contributors:Thipwiwatpotjana, Phantipa, author.
ISBN:9783319511078
3319511076
9783319511054
331951105X
Digital file characteristics:text file
PDF
Notes:Includes bibliographical references.
Online resource; title from PDF title page (SpringerLink, viewed January 27, 2017).
Summary: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 that 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 such a model in detail. All in all, the book provides the readers with the necessary background to understand flexible and generalized uncertainty optimization and develop their own optimization model.
Other form:Print version: Lodwick, Weldon A. Flexible and generalized uncertainty optimization. Cham, Switzerland : Springer, 2017 9783319511054 331951105X
Standard no.:10.1007/978-3-319-51107-8