Sammenlign metoder

	Least-Cost Path / Cost-Distance Analysis	Lokalisasjons-allokeringsmodeller	Teknikk for rangering etter likhet med idealløsning
Fagfelt	Romlig analyse	Romlig analyse	Beslutningstaking
Familie	Process / pipeline	Process / pipeline	MCDM
Opprinnelsesår	1994	1963	1981
Opphavsperson	Edsger Dijkstra (shortest path); GIS cost-surface adaptation	Leon Cooper; S. L. Hakimi	Hwang, C. L., Yoon, K.
Type	Raster cost-surface routing	Spatial facility-location optimization	Distance-based (compromise)
Opprinnelig kilde	Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.	Cooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343.	Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications — A State-of-the-Art Survey. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag
Alias	cost-distance analysis, accumulated cost surface, least-cost corridor, en düşük maliyetli yol	facility location, p-median problem, maximal covering location problem, yer-tahsis modelleri	—
Relaterte	3	4	8
Sammendrag	Least-cost path analysis finds the route between two locations that minimizes accumulated travel cost across a landscape, rather than minimizing straight-line distance. By encoding terrain, slope, land cover, and other frictions into a cost surface and accumulating cost outward from a source, it identifies optimal corridors for roads, pipelines, trails, power lines, and wildlife movement — a core raster-GIS technique built on Dijkstra's shortest-path logic.	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.	TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.