Titlebook: Uncertainty in Facility Location Problems; H. A. Eiselt,Vladimir Marianov Book 2023 The Editor(s) (if applicable) and The Author(s), under

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Vladimir Marianov,Gonzalo Méndez-Vogeletailed therapeutic guidelines for specific rare tumors. The authors are a multidisciplinary group of specialists who have dedicated themselves to this group of tumors.978-3-642-04197-6Series ISSN 1613-5318 Series E-ISSN 2191-0812

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Customer-Related Uncertainties in Facility Location Problemsers about product and store features, and imperfect information on customers available to decision-makers. The effects of these uncertainties on customers’ behavior are also described: purchases distributed among all competitors, comparison shopping, multipurpose trips, and price and feature search.

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Facility Location and Supply Chain Risk Analyticsg in the literature, namely, a missing clear objective and quantifiable definition of risk in supply chain management. Both researchers and practitioners can benefit from the contents of this chapter.

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Uncertainty in Facility Location Models for Emergency Medical Services includes EMS systems with tiered units, systems that consider resource relocation, EMS systems in developing countries, and several other areas. Lastly, it concludes by providing insights into how these models are used in practice.

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Location of Public Facilities Under Congestionations research literature. To organize our view of the current literature, we present a unifying classification of public facility location models with congestion and present relevant models, solution approaches, and their strengths and limitations. We conclude this chapter by discussing the curren

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Stochastic Gradual Covering Location Modelslly covered..In this chapter, we summarize gradual cover models emphasizing on models that have stochastic parameters. We also propose a new model analyzing a stochastic version of the directional graduate cover.

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