Research Article
A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC
Table 10
Global matrix for geometric average for pessimistic and optimistic scenarios.
| DMU | S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | S9 | S10 | S11 |
Average superefficiency | Ranking | 0 | 0.1 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 1 |
| 1 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 2.000 | 4 | 2 | 3.803 | 3.661 | 3.512 | 3.360 | 3.203 | 3.043 | 3.006 | 2.915 | 2.758 | 2.700 | 2.792 | 3.159 | 1 | 3 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 18 | 4 | 1.019 | 1.022 | 1.024 | 1.028 | 1.036 | 1.055 | 1.168 | 1.085 | 1.051 | 1.021 | 1.000 | 1.046 | 16 | 5 | 1.008 | 1.010 | 1.012 | 1.016 | 1.067 | 1.285 | 1.432 | 1.547 | 1.591 | 1.674 | 2.200 | 1.349 | 8 | 6 | 1.281 | 1.278 | 1.269 | 1.258 | 1.248 | 1.238 | 1.228 | 1.219 | 1.209 | 1.200 | 1.191 | 1.238 | 11 | 7 | 0.805 | 0.808 | 0.811 | 0.811 | 0.810 | 0.811 | 0.814 | 0.815 | 0.813 | 0.812 | 0.812 | 0.811 | 24 | 8 | 1.270 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 1.271 | 10 | 9 | 1.016 | 1.015 | 1.014 | 1.013 | 1.012 | 1.010 | 1.009 | 1.009 | 1.009 | 1.009 | 1.009 | 1.011 | 17 | 10 | 1.030 | 1.046 | 1.066 | 1.087 | 1.108 | 1.130 | 1.153 | 1.176 | 1.189 | 1.188 | 1.188 | 1.124 | 15 | 11 | 1.952 | 2.000 | 2.069 | 2.178 | 2.353 | 2.691 | 7.030 | 1.683 | 1.665 | 1.647 | 1.431 | 2.427 | 3 | 12 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 19 | 13 | 0.977 | 0.982 | 0.982 | 0.983 | 0.984 | 0.984 | 0.985 | 0.986 | 0.987 | 0.987 | 0.988 | 0.984 | 22 | 14 | 1.652 | 1.614 | 1.574 | 1.535 | 1.495 | 1.455 | 1.414 | 1.316 | 1.213 | 1.126 | 1.086 | 1.407 | 7 | 15 | 1.539 | 1.555 | 1.566 | 1.582 | 1.614 | 1.649 | 2.709 | 1.953 | 1.854 | 1.655 | 1.578 | 1.750 | 5 | 16 | 1.448 | 1.461 | 1.481 | 1.500 | 1.496 | 1.493 | 1.494 | 1.493 | 1.491 | 1.491 | 1.490 | 1.485 | 6 | 17 | 1.694 | 1.704 | 1.719 | 1.739 | 3.999 | 2.856 | 2.873 | 3.015 | 3.138 | 2.808 | 2.009 | 2.505 | 2 | 18 | 1.106 | 1.114 | 1.123 | 1.132 | 1.142 | 1.152 | 1.164 | 1.169 | 1.173 | 1.176 | 1.176 | 1.148 | 14 | 19 | 0.847 | 0.858 | 0.868 | 0.877 | 0.887 | 0.900 | 0.902 | 0.919 | 0.961 | 0.971 | 0.975 | 0.906 | 23 | 20 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 20 | 21 | 1.313 | 1.316 | 1.318 | 1.318 | 1.315 | 1.316 | 1.318 | 1.322 | 1.337 | 1.352 | 1.400 | 1.330 | 9 | 22 | 1.123 | 1.126 | 1.138 | 1.150 | 1.164 | 1.179 | 1.195 | 1.213 | 1.232 | 1.240 | 1.240 | 1.182 | 13 | 23 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 21 | 24 | 1.235 | 1.231 | 1.227 | 1.224 | 1.220 | 1.216 | 1.213 | 1.210 | 1.207 | 1.205 | 1.205 | 1.218 | 12 | 25 | 0.750 | 0.753 | 0.756 | 0.755 | 0.757 | 0.757 | 0.757 | 0.758 | 0.758 | 0.758 | 0.758 | 0.756 | 25 |
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