This page shows the benchmarks results for the dataset instance “motor11”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -50.16.
Run time 1s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -50.1629 | -50.1637 | yes | 100.00% |
| dd-ls3 | -50.1629 | -50.1954 | yes | 100.00% |
| dd-ls4 | -50.1629 | -50.4658 | yes | 100.00% |
| fgmd | inf | -inf | no | – |
| fm-bca | -50.1629 | -50.1629 | yes | 100.00% |
| fm | -50.1629 | -70.8786 | yes | 100.00% |
| fw | -50.1629 | -inf | yes | 100.00% |
| ga | -50.1629 | -inf | yes | 100.00% |
| hbp | -50.1629 | -51.1384 | yes | 100.00% |
| ipfps | -50.1629 | -inf | yes | 100.00% |
| ipfpu | -48.9401 | -inf | no | 91.30% |
| lsm | -50.1629 | -inf | yes | 100.00% |
| mp | -50.1629 | -50.1629 | yes | 100.00% |
| mp-fw | -50.1629 | -50.1629 | yes | 100.00% |
| mpm | -44.2045 | -inf | no | 73.91% |
| mp-mcf | -50.1629 | -50.1629 | yes | 100.00% |
| pm | -30.6615 | -inf | no | 47.83% |
| rrwm | -50.1629 | -inf | yes | 100.00% |
| sm | -50.1629 | -inf | yes | 100.00% |
| smac | -47.3683 | -inf | no | 91.30% |
Run time 10s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -50.1629 | -50.1637 | yes | 100.00% |
| dd-ls3 | -50.1629 | -50.1954 | yes | 100.00% |
| dd-ls4 | -50.1629 | -50.1757 | yes | 100.00% |
| fgmd | -50.1629 | -inf | yes | 100.00% |
| fm-bca | -50.1629 | -50.1629 | yes | 100.00% |
| fm | -50.1629 | -70.8786 | yes | 100.00% |
| fw | -50.1629 | -inf | yes | 100.00% |
| ga | -50.1629 | -inf | yes | 100.00% |
| hbp | -50.1629 | -51.1384 | yes | 100.00% |
| ipfps | -50.1629 | -inf | yes | 100.00% |
| ipfpu | -48.9401 | -inf | no | 91.30% |
| lsm | -50.1629 | -inf | yes | 100.00% |
| mp | -50.1629 | -50.1629 | yes | 100.00% |
| mp-fw | -50.1629 | -50.1629 | yes | 100.00% |
| mpm | -44.2045 | -inf | no | 73.91% |
| mp-mcf | -50.1629 | -50.1629 | yes | 100.00% |
| pm | -30.6615 | -inf | no | 47.83% |
| rrwm | -50.1629 | -inf | yes | 100.00% |
| sm | -50.1629 | -inf | yes | 100.00% |
| smac | -47.3683 | -inf | no | 91.30% |
Run time 100s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -50.1629 | -50.1637 | yes | 100.00% |
| dd-ls3 | -50.1629 | -50.1954 | yes | 100.00% |
| dd-ls4 | -50.1629 | -50.1757 | yes | 100.00% |
| fgmd | -50.1629 | -inf | yes | 100.00% |
| fm-bca | -50.1629 | -50.1629 | yes | 100.00% |
| fm | -50.1629 | -70.8786 | yes | 100.00% |
| fw | -50.1629 | -inf | yes | 100.00% |
| ga | -50.1629 | -inf | yes | 100.00% |
| hbp | -50.1629 | -51.1384 | yes | 100.00% |
| ipfps | -50.1629 | -inf | yes | 100.00% |
| ipfpu | -48.9401 | -inf | no | 91.30% |
| lsm | -50.1629 | -inf | yes | 100.00% |
| mp | -50.1629 | -50.1629 | yes | 100.00% |
| mp-fw | -50.1629 | -50.1629 | yes | 100.00% |
| mpm | -44.2045 | -inf | no | 73.91% |
| mp-mcf | -50.1629 | -50.1629 | yes | 100.00% |
| pm | -30.6615 | -inf | no | 47.83% |
| rrwm | -50.1629 | -inf | yes | 100.00% |
| sm | -50.1629 | -inf | yes | 100.00% |
| smac | -47.3683 | -inf | no | 91.30% |
Run time 300s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -50.1629 | -50.1637 | yes | 100.00% |
| dd-ls3 | -50.1629 | -50.1954 | yes | 100.00% |
| dd-ls4 | -50.1629 | -50.1757 | yes | 100.00% |
| fgmd | -50.1629 | -inf | yes | 100.00% |
| fm-bca | -50.1629 | -50.1629 | yes | 100.00% |
| fm | -50.1629 | -70.8786 | yes | 100.00% |
| fw | -50.1629 | -inf | yes | 100.00% |
| ga | -50.1629 | -inf | yes | 100.00% |
| hbp | -50.1629 | -51.1384 | yes | 100.00% |
| ipfps | -50.1629 | -inf | yes | 100.00% |
| ipfpu | -48.9401 | -inf | no | 91.30% |
| lsm | -50.1629 | -inf | yes | 100.00% |
| mp | -50.1629 | -50.1629 | yes | 100.00% |
| mp-fw | -50.1629 | -50.1629 | yes | 100.00% |
| mpm | -44.2045 | -inf | no | 73.91% |
| mp-mcf | -50.1629 | -50.1629 | yes | 100.00% |
| pm | -30.6615 | -inf | no | 47.83% |
| rrwm | -50.1629 | -inf | yes | 100.00% |
| sm | -50.1629 | -inf | yes | 100.00% |
| smac | -47.3683 | -inf | no | 91.30% |
Other Results for this Dataset
Accumulated results for whole dataset: motor
Results for individual instances of the dataset: