This page shows the benchmarks results for the dataset instance “car20”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -106.69.
Run time 1s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -106.695 | -106.712 | yes | 100.00% |
| dd-ls3 | -86.6277 | -108.419 | no | 76.74% |
| dd-ls4 | -81.8412 | -111.452 | no | 74.42% |
| fgmd | inf | -inf | no | – |
| fm-bca | -106.695 | -106.695 | yes | 100.00% |
| fm | -106.695 | -143.074 | yes | 100.00% |
| fw | -106.695 | -inf | yes | 100.00% |
| ga | -106.695 | -inf | yes | 100.00% |
| hbp | -106.695 | -107.663 | yes | 100.00% |
| ipfps | -100.363 | -inf | no | 88.37% |
| ipfpu | -98.8611 | -inf | no | 86.05% |
| lsm | -97.8725 | -inf | no | 86.05% |
| mp | -106.695 | -106.695 | yes | 100.00% |
| mp-fw | -106.695 | -106.695 | yes | 100.00% |
| mpm | inf | -inf | no | – |
| mp-mcf | -106.695 | -106.695 | yes | 100.00% |
| pm | -53.4497 | -inf | no | 25.58% |
| rrwm | -106.695 | -inf | yes | 100.00% |
| sm | -106.695 | -inf | yes | 100.00% |
| smac | -83.1624 | -inf | no | 72.09% |
Run time 10s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -106.695 | -106.712 | yes | 100.00% |
| dd-ls3 | -106.695 | -106.702 | yes | 100.00% |
| dd-ls4 | -106.695 | -106.785 | yes | 100.00% |
| fgmd | -106.695 | -inf | yes | 100.00% |
| fm-bca | -106.695 | -106.695 | yes | 100.00% |
| fm | -106.695 | -143.074 | yes | 100.00% |
| fw | -106.695 | -inf | yes | 100.00% |
| ga | -106.695 | -inf | yes | 100.00% |
| hbp | -106.695 | -107.663 | yes | 100.00% |
| ipfps | -100.363 | -inf | no | 88.37% |
| ipfpu | -98.8611 | -inf | no | 86.05% |
| lsm | -97.8725 | -inf | no | 86.05% |
| mp | -106.695 | -106.695 | yes | 100.00% |
| mp-fw | -106.695 | -106.695 | yes | 100.00% |
| mpm | -89.9964 | -inf | no | 74.42% |
| mp-mcf | -106.695 | -106.695 | yes | 100.00% |
| pm | -53.4497 | -inf | no | 25.58% |
| rrwm | -106.695 | -inf | yes | 100.00% |
| sm | -106.695 | -inf | yes | 100.00% |
| smac | -83.1624 | -inf | no | 72.09% |
Run time 100s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -106.695 | -106.712 | yes | 100.00% |
| dd-ls3 | -106.695 | -106.702 | yes | 100.00% |
| dd-ls4 | -106.695 | -106.708 | yes | 100.00% |
| fgmd | -106.695 | -inf | yes | 100.00% |
| fm-bca | -106.695 | -106.695 | yes | 100.00% |
| fm | -106.695 | -143.074 | yes | 100.00% |
| fw | -106.695 | -inf | yes | 100.00% |
| ga | -106.695 | -inf | yes | 100.00% |
| hbp | -106.695 | -107.663 | yes | 100.00% |
| ipfps | -100.363 | -inf | no | 88.37% |
| ipfpu | -98.8611 | -inf | no | 86.05% |
| lsm | -97.8725 | -inf | no | 86.05% |
| mp | -106.695 | -106.695 | yes | 100.00% |
| mp-fw | -106.695 | -106.695 | yes | 100.00% |
| mpm | -89.9964 | -inf | no | 74.42% |
| mp-mcf | -106.695 | -106.695 | yes | 100.00% |
| pm | -53.4497 | -inf | no | 25.58% |
| rrwm | -106.695 | -inf | yes | 100.00% |
| sm | -106.695 | -inf | yes | 100.00% |
| smac | -83.1624 | -inf | no | 72.09% |
Run time 300s
| method | value | bound | optimal | accuracy |
|---|---|---|---|---|
| dd-ls0 | -106.695 | -106.712 | yes | 100.00% |
| dd-ls3 | -106.695 | -106.702 | yes | 100.00% |
| dd-ls4 | -106.695 | -106.708 | yes | 100.00% |
| fgmd | -106.695 | -inf | yes | 100.00% |
| fm-bca | -106.695 | -106.695 | yes | 100.00% |
| fm | -106.695 | -143.074 | yes | 100.00% |
| fw | -106.695 | -inf | yes | 100.00% |
| ga | -106.695 | -inf | yes | 100.00% |
| hbp | -106.695 | -107.663 | yes | 100.00% |
| ipfps | -100.363 | -inf | no | 88.37% |
| ipfpu | -98.8611 | -inf | no | 86.05% |
| lsm | -97.8725 | -inf | no | 86.05% |
| mp | -106.695 | -106.695 | yes | 100.00% |
| mp-fw | -106.695 | -106.695 | yes | 100.00% |
| mpm | -89.9964 | -inf | no | 74.42% |
| mp-mcf | -106.695 | -106.695 | yes | 100.00% |
| pm | -53.4497 | -inf | no | 25.58% |
| rrwm | -106.695 | -inf | yes | 100.00% |
| sm | -106.695 | -inf | yes | 100.00% |
| smac | -83.1624 | -inf | no | 72.09% |
Other Results for this Dataset
Accumulated results for whole dataset: car
Results for individual instances of the dataset: