04166nam a22006135i 4500 978-3-031-55927-3 DE-He213 20251030112255.0 cr nn 008mamaa 240603s2024 sz | s |||| 0|eng d 9783031559273 978-3-031-55927-3 10.1007/978-3-031-55927-3 doi TS155-194 KJMV bicssc BUS087000 bisacsh KJMV thema Saldanha-da-Gama, Francisco. author. aut http://id.loc.gov/vocabulary/relators/aut 78177 Facility Location Under Uncertainty [electronic resource] : Models, Algorithms and Applications / by Francisco Saldanha-da-Gama, Shuming Wang. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XVI, 534 p. 22 illus., 9 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda International Series in Operations Research & Management Science, 2214-7934 ; 356 Introduction -- Principles and Background -- Discrete Facility Location Problems -- Decision Making under Uncertainty: Ingredients for Modeling -- Optimization under Uncertainty -- Modeling Paradigms and Solution Techniques -- Robust Facility Location -- Stochastic Facility Location -- Facility Location with Chance Constraints -- Distributionally Robust Facility Location -- Extended Models -- Location-Inventory Problems -- Facility Location with Routing Decisions -- Hub Location -- Logistics and Supply Chain Management -- Territory Design -- Comprehensive Uncertainty with Applications -- Bilevel Recycling Facility Location -- Multi-Period Hub Location with Time Series -- Data-Driven Robust Production Planning. 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, and location inventory. Production management. 67141 Operations research. 57943 Management science. 57941 Mathematical optimization. 65522 Business logistics. 61225 Operations Management. 67304 Operations Research and Decision Theory. 67143 Operations Research, Management Science. 65527 Optimization. 65528 Supply Chain Management. 66371 Logistics. 68350 Wang, Shuming. author. aut http://id.loc.gov/vocabulary/relators/aut 78178 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031559266 Printed edition: 9783031559280 Printed edition: 9783031559297 International Series in Operations Research & Management Science, 2214-7934 ; 356 69480 https://doi.org/10.1007/978-3-031-55927-3 ZDB-2-BUM ZDB-2-SXBM 60480 60480