方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 区位-分配模型× | 基于地理信息系统的多准则决策分析 (GIS-MCDA)× | 整数规划× | |
|---|---|---|---|
| 领域≠ | 空间分析 | 空间分析 | 优化 |
| 方法族 | Process / pipeline | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1963 | 2006 | 1958 |
| 提出者≠ | Leon Cooper; S. L. Hakimi | Jacek Malczewski (GIS-MCDA synthesis) | Ralph Gomory (cutting planes, 1958); land-and-doig branch-and-bound (1960) |
| 类型≠ | Spatial facility-location optimization | Spatial multi-criteria suitability/decision analysis | Mathematical optimisation — exact combinatorial method |
| 开创性文献≠ | Cooper, 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: 9780471283669 |
| 别名≠ | facility location, p-median problem, maximal covering location problem, yer-tahsis modelleri | GIS-MCDM, spatial multi-criteria analysis, GIS-AHP, weighted overlay suitability | IP, MIP, mixed-integer programming, mixed-integer linear programming |
| 相关 | 4 | 4 | 4 |
| 摘要≠ | 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. | 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. |
| ScholarGate数据集 ↗ |
|
|
|