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로케이션-할당 모델×지리정보시스템 기반 다기준 의사결정 분석 (GIS-MCDA)×정수 계획법(IP) 및 혼합 정수 계획법(MIP)×최소 비용 경로 / 비용 거리 분석×
분야공간분석공간분석최적화공간분석
계열Process / pipelineProcess / pipelineProcess / pipelineProcess / pipeline
기원 연도1963200619581994
창시자Leon 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
유형Spatial facility-location optimizationSpatial multi-criteria suitability/decision analysisMathematical optimisation — exact combinatorial methodRaster cost-surface routing
원전Cooper, 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 ↗
별칭facility 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
관련4443
요약Location-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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ScholarGate방법 비교: Location-Allocation · GIS-MCDA · Integer Programming · Least-Cost Path. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare