방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 두 벡터 간의 맨해튼 거리× | 조합 거리 기반 평가× | |
|---|---|---|
| 분야 | 의사결정 | 의사결정 |
| 계열 | MCDM | MCDM |
| 기원 연도≠ | 2020 | 2016 |
| 창시자≠ | Dezert, J., Tchamova, A., Han, D., Bhotto, M. Z. A. | Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. |
| 유형≠ | Distance (L1, city-block) | Distance from anti-ideal (Euclidean + Taxicab) |
| 원전≠ | Dezert, J., Tchamova, A., Han, D., Bhotto, M. Z. A. (2020). Manhattan Distance. IEEE Transactions on Cybernetics link ↗ | Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation and Economic Cybernetics Studies and Research link ↗ |
| 별칭 | — | — |
| 관련≠ | 1 | 8 |
| 요약≠ | DIST-MANHATTAN (Manhattan Distance — L1 norm (city-block distance) between two vectors) is a distance multi-criteria decision-making (MCDM) method introduced by Dezert, J., Tchamova, A., Han, D., Bhotto, M. Z. A. in 2020. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | CODAS (Combinative Distance-Based Assessment) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J. in 2016. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGate데이터셋 ↗ |
|
|