Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Min-Max Normalization× | Сравнение по площади границы приближения для множества атрибутов× | |
|---|---|---|
| Область | Принятие решений | Принятие решений |
| Семейство | MCDM | MCDM |
| Год появления≠ | 1981 | 2015 |
| Автор метода≠ | Hwang, C. L., Yoon, K. | Pamučar, D., Ćirović, G. |
| Тип≠ | Normalization (linear, range-scaling) | Border approximation area (distance from BAA) |
| Основополагающий источник≠ | Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗ | Pamučar, D., Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications DOI ↗ |
| Другие названия | — | — |
| Связанные | 8 | 8 |
| Сводка≠ | MIN-MAX-NORMALIZATION (Min-Max Normalization — linear rescaling of each criterion column to [0, 1]) is a normalization multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | MABAC (Multi-Attributive Border Approximation area Comparison) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D., Ćirović, G. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateНабор данных ↗ |
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