Σύγκριση μεθόδων

	Ανάλυση Πολλαπλών Κριτηρίων Βάσει ΓΣΠ (GIS-MCDA)	Ακέραιος Προγραμματισμός	Ελάχιστο Κόστος Διαδρομής / Ανάλυση Απόστασης Κόστους
Πεδίο	Χωρική Ανάλυση	Βελτιστοποίηση	Χωρική Ανάλυση
Οικογένεια	Process / pipeline	Process / pipeline	Process / pipeline
Έτος προέλευσης	2006	1958	1994
Δημιουργός	Jacek Malczewski (GIS-MCDA synthesis)	Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)	Edsger Dijkstra (shortest path); GIS cost-surface adaptation
Τύπος	Spatial multi-criteria suitability/decision analysis	Mathematical optimisation — exact combinatorial method	Raster cost-surface routing
Θεμελιώδης πηγή	Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.	Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669	Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.
Εναλλακτικές ονομασίες	GIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitability	IP, MIP, mixed-integer programming, mixed-integer linear programming	cost-distance analysis, accumulated cost surface, least-cost corridor, en düşük maliyetli yol
Συναφείς	4	4	3
Σύνοψη	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.	Integer programming (IP), also called mixed-integer programming (MIP) when only some variables are restricted to whole numbers, is a branch of mathematical optimisation in which some or all decision variables must take integer or binary values. Building on linear programming, it was formalised through Ralph Gomory's cutting-plane method (1958) and the Land-and-Doig branch-and-bound algorithm (1960), and it has since become the standard exact framework for scheduling, assignment, routing, and resource-allocation problems.	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.