Flexible and generalized uncertainty optimization : theory and methods

• Main Authors: Lodwick, Weldon A., (Author), Thipwiwatpotjana, Phantipa, (Author)
• Format: eBook
• Language: English
• Published: Cham, Switzerland : Springer, 2017.
• Series: Studies in computational intelligence ; v. 696.
• Subjects: Mathematical optimization.; Uncertainty (Information theory); Fuzzy sets.; elektronické knihy; electronic books
• ISBN: 9783319511078; 9783319511054
• Physical Description: 1 online resource (x, 190 pages) : illustrations (some color)
• ISSN: 1860-949X
• Access: Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty

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.