Σύγκριση μεθόδων

	Μοντέλα Τοποθέτησης-Διάθεσης (Location-Allocation Models)	Μοντέλο Ακτινοβολίας Κινητικότητας και Μετανάστευσης	Μοντέλα Χωρικής Αλληλεπίδρασης (Βαρύτητας)
Πεδίο	Χωρική Ανάλυση	Χωρική Ανάλυση	Χωρική Ανάλυση
Οικογένεια	Process / pipeline	Regression model	Regression model
Έτος προέλευσης	1963	2012	1971
Δημιουργός	Leon Cooper; S. L. Hakimi	Filippo Simini et al.	Alan Wilson (entropy-maximizing family)
Τύπος	Spatial facility-location optimization	Parameter-free spatial interaction model	Model of flows between spatial origins and destinations
Θεμελιώδης πηγή	Cooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343.	Simini, F., González, M. C., Maritan, A., & Barabási, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100.	Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32.
Εναλλακτικές ονομασίες	facility location, p-median problem, maximal covering location problem, yer-tahsis modelleri	Radiation Law of Human Mobility, Parameter-free Mobility Model, Simini Radiation Model, Radyasyon Modeli	gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
Συναφείς	4	3	4
Σύνοψη	Location-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.	The Radiation Model, introduced by Simini et al. in 2012, is a parameter-free model for predicting human mobility and migration flows between geographic locations. Drawing an analogy from radiation physics, it predicts trip volumes based solely on population sizes at origin and destination, and the intervening population within the circle connecting them. It has been widely applied to commuting flows, migration, and epidemic spreading.	Spatial interaction models predict the volume of flows — migrants, commuters, shoppers, trade, trips — between origins and destinations as a function of the size of each place and the distance or cost separating them. By analogy to Newton's gravity, interaction rises with the 'mass' of origin and destination and falls with separation, and Wilson's 1971 entropy-maximizing family put these models on a rigorous footing for transport, migration, and retail analysis.