Classical Benchmarks
References
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1. Asta, S., Özcan, E., and Curtois, T. A tensor based hyper-heuristic for nurse rostering. Knowledge-based systems, 2016. 98: p. 185-199.
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2. Burke E.K. and T. Curtois. New Approaches to Nurse Rostering Benchmark Instances. European Journal of Operational Research, 2014. 237(1): p. 71-81. pdf.
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3. Solos, Ioannis P., Ioannis X. Tassopoulos and Grigorios N. Beligiannis. A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively Solving the Nurse Rostering Problem. Algorithms, 2013. 6: p. 278-308.
Speed Comparison
Optimality Proven Instances
| Instance Name | Cplex | Gurobi | AutoRoster | ScheduleNurse3 |
|---|---|---|---|---|
| QMC-1 | 2.95/2.25=1.3 | 2.25/2.25=1 | - | 8.5/2.25=3.8 |
| SINTEF | 1.89/0.78=2.4 | 0.78/0.78=1 | 9/0.78=11.5 | 1.15/0.78=1.5 |
| ikegami-3Shift-DATA1.2 | - | 695/5.66=122.8 | - | 5.66/5.66=1 |
| ikegami-3Shift-DATA1.1 | 6606/7.155=923.3 | 416/7.155=58.1 | - | 7.155/7.155=1 |
| ikegami-3Shift-DATA1 | 1838/4=459.5 | 285/4=71.3 | - | 4/4=1 |
| ikegami-2Shift-DATA1 | 9.23/0.14=65.9 | 0.14/0.14=1 | 11/0.14=78.6 | 1.94/0.14=13.9 |
| GPOST-B | 227/34=6.7 | 161/34=4.7 | 40/34=1.2 | 34/34=1 |
| GPOST | 124/2.8=44.3 | 22/2.8=7.9 | 17/2.8=6.1 | 2.8/2.8=1 |
| Valouxis-1 | - | - | - | 37/37=1 |
| WHPP | - | 4853/4=1213.3 | 17/4=4.3 | 4/4=1 |
| BCDT-Sep | - | - | - | 140/140=1 |
Optimal Objective Reached Instances
| Instance Name | Cplex | Gurobi | AutoRoster | ScheduleNurse3 |
|---|---|---|---|---|
| QMC-1 | 2.95/2.25=1.3 | 2.25/2.25=1 | 140/2.25=62.2 | 8.5/2.25=3.8 |
| SINTEF | 1.89/0.78=2.4 | 0.78/0.78=1 | 9/0.78=11.5 | 1.146/0.78=1.5 |
| ikegami-3Shift-DATA1.2 | 2573/4=643.3 | 184/4=46 | - | 4/4=1 |
| ikegami-3Shift-DATA1.1 | 6606/3.94=1676.6 | 175/3.94=44.4 | - | 3.94/3.94=1 |
| ikegami-3Shift-DATA1 | 1200/4=300 | 285/4=71.3 | 300/4=75 | 4/4=1 |
| ikegami-2Shift-DATA1 | 9.23/0.14=65.9 | 0.14/0.14=1 | 11/0.14=78.6 | 1.94/0.14=13.9 |
| GPOST-B | 130/2.5=52 | 61/2.5=24.4 | 40/2.5=16 | 2.5/2.5=1 |
| GPOST | 124/2.3=53.9 | 22/2.3=9.6 | 17/2.3=7.4 | 2.3/2.3=1 |
| Valouxis-1 | 663/3.91=170 | 224/3.91=57.3 | 9/3.91=2.3 | 3.91/3.91=1 |
| WHPP | - | 4853/4=1213.3 | 17/4=4.3 | 4/4=1 |
| BCDT-Sep | - | - | - | 140/140=1 |
Time - Number of Instances proven optimality
| No. | Instance Name |
|---|---|
| 1 | Millar-2Shift-DATA1.1 |
| 2 | Millar-2Shift-DATA1 |
| 3 | Ozkarahan |
| 4 | Musa |
| 5 | Azaiez |
| 6 | QMC-1 |
| 7 | LLR |
| 8 | SINTEF |
| 9 | ikegami-3Shift-DATA1.2 |
| 10 | ikegami-3Shift-DATA1.1 |
| 11 | ikegami-3Shift-DATA1 |
| 12 | ikegami-2Shift-DATA1 |
| 13 | GPOST-B |
| 14 | BCV-4.13.1 |
| 15 | GPOST |
| 16 | Valouxis-1 |
| 17 | WHPP |
| 18 | BCDT-Sep |
Time - Number of Instances reached optimal objective
| No. | Instance Name |
|---|---|
| 1 | Millar-2Shift-DATA1.1 |
| 2 | Millar-2Shift-DATA1 |
| 3 | Ozkarahan |
| 4 | Musa |
| 5 | Azaiez |
| 6 | QMC-1 |
| 7 | LLR |
| 8 | SINTEF |
| 9 | ikegami-3Shift-DATA1.2 |
| 10 | ikegami-3Shift-DATA1.1 |
| 11 | ikegami-3Shift-DATA1 |
| 12 | ikegami-2Shift-DATA1 |
| 13 | GPOST-B |
| 14 | BCV-4.13.1 |
| 15 | GPOST |
| 16 | Valouxis-1 |
| 17 | WHPP |
| 18 | BCDT-Sep |
Detail Data
