| 书目名称 | Facility Location Under Uncertainty | | 副标题 | Models, Algorithms a | | 编辑 | Francisco Saldanha-da-Gama,Shuming Wang | | 视频video | | | 概述 | Provides the first comprehensive introduction on Facility Location under Uncertainty.Discusses facility location models under modern developing trends.Discloses the future research directions | | 丛书名称 | International Series in Operations Research & Management Science | | 图书封面 |  | | 描述 | .This textbook provides researchers, post-graduate students, and practitioners with a systematic framework for coping with uncertainty when making facility location decisions. In addition to in-depth coverage of models and solution techniques, application areas are discussed. . .The book guides readers through the field, showing how to successfully analyze new problems and handle new applications. Initially, the focus is on base models and concepts. Then, gradually, more comprehensive models and more involved solution algorithms are discussed. Throughout the book, two perspectives are intertwined: the paradigm for capturing uncertainty, and the facility location problem at hand. The former includes stochastic programming, robust optimization, chance-constrained programming, and distributional robust optimization; the latter includes classical facility location problems and those arising in many real-world applications such as hub location, location routing, andlocation inventory.. | | 出版日期 | Textbook 2024 | | 关键词 | Decision Making; Engineering Design; Expert Ranking; Aggregation Technique; Ranking Aggregation | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-55927-3 | | isbn_softcover | 978-3-031-55929-7 | | isbn_ebook | 978-3-031-55927-3Series ISSN 0884-8289 Series E-ISSN 2214-7934 | | issn_series | 0884-8289 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 17:08:53
