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| GIS-MCDA× | Целобројно програмирање× | Linearno programiranje× | |
|---|---|---|---|
| Oblast≠ | Prostorna analiza | Optimizacija | Optimizacija |
| Porodica | Process / pipeline | Process / pipeline | Process / pipeline |
| Godina nastanka≠ | 2006 | 1958 | 1947 |
| Tvorac≠ | Jacek Malczewski (GIS-MCDA synthesis) | Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960) | George B. Dantzig |
| Tip≠ | Spatial multi-criteria suitability/decision analysis | Mathematical optimisation — exact combinatorial method | Mathematical programming / continuous optimization |
| Temeljni izvor≠ | 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: 9780471283669 | Dantzig, G.B. (1963). Linear Programming and Extensions. Princeton University Press. ISBN: 9780691059136 |
| Drugi nazivi≠ | GIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitability | IP, MIP, mixed-integer programming, mixed-integer linear programming | LP, linear optimization, Doğrusal Programlama (LP) |
| Srodne | 4 | 4 | 4 |
| Sažetak≠ | 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. | Linear programming (LP), pioneered by George B. Dantzig in 1947, is a mathematical method for finding the best value of a linear objective function — such as minimum cost or maximum profit — subject to a set of linear inequality and equality constraints. It is the foundational technique in operations research and underlies production planning, resource allocation, logistics, diet problems, and countless other decision-making scenarios across engineering, economics, and the natural sciences. |
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