方法对比

	Huff 模型	区位-分配模型	辐射模型（Radiation Model）	空间交互（引力）模型
领域	空间分析	空间分析	空间分析	空间分析
方法族	Regression model	Process / pipeline	Regression model	Regression model
起源年份	1964	1963	2012	1971
提出者	David Huff	Leon Cooper; S. L. Hakimi	Filippo Simini et al.	Alan Wilson (entropy-maximizing family)
类型	Probabilistic spatial interaction model	Spatial facility-location optimization	Parameter-free spatial interaction model	Model of flows between spatial origins and destinations
开创性文献	Huff, D. L. (1964). Defining and estimating a trading area. Journal of Marketing, 28(3), 34–38.	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.
别名	Huff Gravity Model, Probabilistic Retail Gravity Model, Huff Trade Area Model, Huff Çekim Modeli	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
相关	3	4	3	4
摘要	Proposed by David Huff in 1964, the Huff Model is a probabilistic spatial interaction model that estimates the likelihood that consumers located in a given geographic zone will choose to shop at a particular retail outlet. It extends deterministic gravity models by assigning each consumer zone a probability of patronage across all competing stores, weighting store attractiveness (typically measured by floor area) against the friction of travel time or distance. The model is widely used in retail site selection, trade area delineation, and market share forecasting.	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.