Models, Algorithms and Applications Saldanha-da-Gama, Francisco. creator author. aut http://id.loc.gov/vocabulary/relators/aut Wang, Shuming. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XVI, 534 p. 22 illus., 9 illus. in color. online resource. 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. 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. by Francisco Saldanha-da-Gama, Shuming Wang. Production management Operations research Management science Mathematical optimization Business logistics Operations Management Operations Research and Decision Theory Operations Research, Management Science Optimization Supply Chain Management Logistics TS155-194 9783031559273 https://doi.org/10.1007/978-3-031-55927-3 https://doi.org/10.1007/978-3-031-55927-3 240603 20251030112255.0 978-3-031-55927-3