Multi-attribute decision-making methods based on normal random variables in supply chain risk management
30 gru 2021
O artykule
Data publikacji: 30 gru 2021
Zakres stron: 719 - 728
Otrzymano: 17 cze 2021
Przyjęty: 24 wrz 2021
DOI: https://doi.org/10.2478/amns.2021.2.00147
Słowa kluczowe
© 2021 Siqi Shen, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Fig. 1

Fig. 2

Fig. 3

The six attribute values of the four robots
2 | 2.5 | [55,56] | [94,114] | Normal (0.4, 0.5, 0.6) | Very high (0.85, 0.9, 0.95, 1) | |
2.5 | 2.7 | [30,40] | [84,104] | Low (0.2, 0.3, 0.4) | Normal (0.3, 0.4, 0.6, 0.7) | |
1.8 | 2.4 | [50,60] | [100,120] | High (0.6, 0.7, 0.8) | High (0.5, 0.6, 0.8, 0.9) | |
2.2 | 2.6 | [35,45] | [90,110] | Normal (0.4, 0.5, 0.6) | Normal (0.3, 0.4, 0.6, 0.7) |
β influence on the closeness of each plan
0 | 0.6726 | 0.0944 | 0.7366 | 0.3451 |
0.2 | 0.6705 | 0.0994 | 0.7358 | 0.3472 |
0.4 | 0.6683 | 0.1053 | 0.735 | 0.3496 |
0.6 | 0.666 | 0.1118 | 0.734 | 0.3522 |
0.8 | 0.6637 | 0.1191 | 0.7329 | 0.355 |
1 | 0.6613 | 0.1296 | 0.7316 | 0.358 |