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מודלים של הקצאת מיקום×ניתוח החלטות רב-קריטריוני מבוסס מערכות מידע גאוגרפי (GIS-MCDA)×תכנון בשלמים×ניתוח נתיב בעלות מינימלית / ניתוח מרחק-עלות×
תחוםניתוח מרחביניתוח מרחביאופטימיזציהניתוח מרחבי
משפחהProcess / pipelineProcess / pipelineProcess / pipelineProcess / pipeline
שנת המקור1963200619581994
הוגה השיטהLeon Cooper; S. L. HakimiJacek Malczewski (GIS-MCDA synthesis)Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960)Edsger Dijkstra (shortest path); GIS cost-surface adaptation
סוגSpatial facility-location optimizationSpatial multi-criteria suitability/decision analysisMathematical optimisation — exact combinatorial methodRaster cost-surface routing
מקור מכונןCooper, L. (1963). Location-allocation problems. Operations Research, 11(3), 331–343. DOI ↗Malczewski, J. (2006). GIS-based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726. DOI ↗Wolsey, L.A. (1998). Integer Programming. Wiley. ISBN: 9780471283669Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271. DOI ↗
כינוייםfacility location, p-median problem, maximal covering location problem, yer-tahsis modelleriGIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitabilityIP, MIP, mixed-integer programming, mixed-integer linear programmingcost-distance analysis, accumulated cost surface, least-cost corridor, en düşük maliyetli yol
קשורות4443
תקצירLocation-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.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.
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ScholarGateהשוואת שיטות: Location-Allocation · GIS-MCDA · Integer Programming · Least-Cost Path. אוחזר בתאריך 2026-06-15 מתוך https://scholargate.app/he/compare