เปรียบเทียบวิธี

	การวิเคราะห์การตัดสินใจหลายเกณฑ์โดยใช้ระบบสารสนเทศภูมิศาสตร์ (GIS-MCDA)	แบบจำลองการจัดสรรตำแหน่งที่ตั้ง (Location-Allocation Models)	การถดถอยโลจิสติกส์หลายตัวแปร (Multinomial Logistic Regression)
สาขาวิชา	การวิเคราะห์เชิงพื้นที่	การวิเคราะห์เชิงพื้นที่	เศรษฐมิติ
ตระกูล	Process / pipeline	Process / pipeline	Regression model
ปีกำเนิด	2006	1963	1974
ผู้ริเริ่ม	Jacek Malczewski (GIS-MCDA synthesis)	Leon Cooper; S. L. Hakimi	McFadden
ประเภท	Spatial multi-criteria suitability/decision analysis	Spatial facility-location optimization	Multinomial logistic regression
แหล่งต้นตำรับ	Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.	Cooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343.	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
ชื่อเรียกอื่น	GIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitability	facility location, p-median problem, maximal covering location problem, yer-tahsis modelleri	multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon
ที่เกี่ยวข้อง	4	4	5
สรุป	GIS-MCDA combines the map layers of a geographic information system with multi-criteria decision analysis to produce suitability or priority maps — ranking locations by how well they satisfy several weighted criteria at once. It is the standard framework for spatial decisions such as siting hospitals, solar farms, landfills, or evacuation areas, integrating methods like AHP, TOPSIS, and weighted overlay with spatial data.	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.	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.