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Modèles de localisation-affectation×Régression logistique multinomiale×
DomaineAnalyse spatialeÉconométrie
FamilleProcess / pipelineRegression model
Année d'origine19631974
Auteur d'origineLeon Cooper; S. L. HakimiMcFadden
TypeSpatial facility-location optimizationMultinomial logistic regression
Source fondatriceCooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343. DOI ↗McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503
Aliasfacility location, p-median problem, maximal covering location problem, yer-tahsis modellerimultinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
Apparentées45
RésuméLocation-allocation models decide where to place a set of facilities and simultaneously assign demand points to them so as to optimize an objective such as total travel cost, worst-case distance, or population covered. Rooted in the operations-research work of Cooper (1963) and Hakimi (1964) and central to network GIS, they answer questions like where to site warehouses, hospitals, fire stations, or schools to best serve a spatially distributed population.Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category.
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Location-Allocation · Multinomial Logit. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare