| 书目名称 | Flexible and Generalized Uncertainty Optimization |
| 副标题 | Theory and Methods |
| 编辑 | Weldon A. Lodwick,Phantipa Thipwiwatpotjana |
| 视频video | |
| 概述 | Unifies both fuzzy and possibilistic optimization.Shows how to construct input data for use in flexible and generalized uncertainty optimization problems.Presents practical, theoretical and historical |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | .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. . |
| 出版日期 | Book 20171st edition |
| 关键词 | Fuzzy Intervals; Possibility Intervals; Necessity Measures; Interval-valued probabilities; Kolmogorov-Sm |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-51107-8 |
| isbn_ebook | 978-3-319-51107-8Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 16:18:28
