Worked examples: every method, with expected results
Each example gives the file, the settings and the ranking to expect; Open in the evaluator loads the file with the method already chosen (step 6), so that the settings can be checked and the run repeated. The results are those of the verification examples of the User Guide (section 6), the GUI Tutorial (section 4) and the Method Reference; they were produced by the engine when this page was built.
1. Weighted Average Method (WAM) - NIJKAMP.MCE
The Nijkamp example of the User Guide, section 6.1. Settings: standardization 1; weights divided by the group sum. The largest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 1 | 0.6 | 11.111 % | ||
| 2 | 2 | 0.533333 | 42.500 % | ||
| 3 | 3 | 0.306667 | 0.000 % |
2. PROMETHEE II - PROM_EX.MCE
The six-alternative example of Brans, Vincke & Mareschal (1986). Settings: standardization 0; weights as given (raw). The largest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 5 | 1.4645 | 94.141 % | ||
| 2 | 2 | 0.0858107 | 216.550 % | ||
| 3 | 4 | -0.100013 | 174.324 % | ||
| 4 | 6 | -0.274359 | 63.151 % | ||
| 5 | 3 | -0.447618 | 62.710 % | ||
| 6 | 1 | -0.72832 | 0.000 % |
3. Compromise Programming (CP) - COMP_HAN.MCE
The Han River example with s = 2 and the provided limits. Settings: standardization 0; weights as given (raw); cp_power = 2, cp_use_provided_limits = True. The smallest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 4 | 1.29546 | 16.308 % | ||
| 2 | 8 | 1.50672 | 19.177 % | ||
| 3 | 9 | 1.79565 | 5.969 % | ||
| 4 | 3 | 1.90283 | 2.424 % | ||
| 5 | 5 | 1.94896 | 8.634 % | ||
| 6 | 7 | 2.11724 | 4.805 % | ||
| 7 | 6 | 2.21899 | 43.403 % | ||
| 8 | 2 | 3.1821 | 143.491 % | ||
| 9 | 1 | 7.74812 | 0.000 % |
4. ELECTRE II - ELEC_EX.MCE
The five-alternative ELECTRE II example of the dissertation. Settings: standardization 0; weights as given (raw). The smallest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 3 | 1 | 100.000 % | ||
| 2 | 1 | 2 | 25.000 % | ||
| 3 | 5 | 2.5 | 20.000 % | ||
| 4 | 2 | 3 | 33.333 % | ||
| 5 | 4 | 4 | 0.000 % |
5. Analytic Hierarchy Process (AHP) - AHP_EXM3.MCE
The Saaty pair-wise comparison example (Appendix 2 of the dissertation). Settings: standardization 0; weights divided by the group sum. The largest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 1 | 0.401928 | 14.297 % | ||
| 2 | 2 | 0.344462 | 26.375 % | ||
| 3 | 3 | 0.25361 | 0.000 % |
6. Expected Value (EV) - NIJKAMP.MCE
The Nijkamp example, ordinal weights and scores. Settings: standardization 1; weights divided by the group sum. The largest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 2 | 0.583333 | 9.524 % | ||
| 2 | 1 | 0.527778 | 26.316 % | ||
| 3 | 3 | 0.388889 | 0.000 % |
7. Regime Analysis (RA) - NIJKAMP.MCE
The Nijkamp example, regime probabilities over the ordinal weight set. Settings: standardization 1; weights divided by the group sum. The largest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 1 | 1 | 50.000 % | ||
| 2 | 2 | 0.5 | 100.000 % | ||
| 3 | 3 | 0 | 0.000 % |
8. TOPSIS - NIJKAMP.MCE
The Nijkamp example, closeness to the ideal and the anti-ideal. Settings: standardization 1; weights divided by the group sum. The largest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 1 | 0.552959 | 3.032 % | ||
| 2 | 2 | 0.536191 | 37.081 % | ||
| 3 | 3 | 0.337365 | 0.000 % |
9. VIKOR - NIJKAMP.MCE
The Nijkamp example, compromise index Q with v = 0.5. Settings: standardization 1; weights divided by the group sum; vikor_v = 0.5. The smallest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 2 | 0.113636 | 340.000 % | ||
| 2 | 1 | 0.5 | 100.000 % | ||
| 3 | 3 | 1 | 0.000 % |
The run issues 1 warning(s), e.g. "VIKOR: condition C1 (acceptable advantage) not satisfied; the compromise set is {2, 1} rather than a single alternative (see vikor.txt).".
10. ELECTRE III - ELEC_HAN.MCE
The Han River ELECTRE example with the thresholds of the file. Settings: standardization 1; weights divided by the group sum. The smallest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 8 | 1 | 50.000 % | ||
| 2 | 9 | 1.5 | 100.000 % | ||
| 3 | 4 | 3 | 16.667 % | ||
| 4 | 2 | 3.5 | 0.000 % | ||
| 4 | 3 | 3.5 | 0.000 % | ||
| 4 | 6 | 3.5 | 0.000 % | ||
| 4 | 7 | 3.5 | 14.286 % | ||
| 5 | 5 | 4 | 12.500 % | ||
| 6 | 1 | 4.5 | 0.000 % |
11. Compromise Programming (CP) invoked as SPOTIS - COMP_HAN.MCE
The Han River example as SPOTIS: CP with the provided limits and s = 1. Settings: standardization 0; weights as given (raw). The smallest value is best. Open in the evaluator
| Rank | Alternative | Name | Ranking value | Domination | Note |
|---|---|---|---|---|---|
| 1 | 8 | 2.24765 | 7.718 % | ||
| 2 | 9 | 2.42113 | 21.622 % | ||
| 3 | 4 | 2.94463 | 0.438 % | ||
| 4 | 5 | 2.95754 | 17.484 % | ||
| 5 | 7 | 3.47464 | 9.774 % | ||
| 6 | 3 | 3.81427 | 3.142 % | ||
| 7 | 6 | 3.93411 | 13.984 % | ||
| 8 | 2 | 4.48424 | 28.926 % | ||
| 9 | 1 | 5.78134 | 0.000 % |