New Nurse Rostering Benchmark Instances
References
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3. 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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4. Strandmark, P., Qu, Y. and Curtois, T. First-order linear programming in a column generation-based heuristic approach to the nurse rostering problem. Computers & Operations Research, 2020. 120, p. 104945. (pdf)
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5. Demirović, E., Musliu, N., and Winter, F. Modeling and solving staff scheduling with partial weighted maxSAT. Annals of Operations Research, 2019. 275(1): p. 79-99.
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6. Smet P. Constraint reformulation for nurse rostering problems, in: PATAT 2018 twelfth international conference on the practice and theory of automated timetabling, Vienna, August, 2018, p. 69-80.
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7. Rahimian, E., Akartunalı, K., and Levine, J. A hybrid integer programming and variable neighbourhood search algorithm to solve nurse rostering problems. European Journal of Operational Research, 2017. 258(2): p. 411-423.
Speed Comparison
Optimality Proven Instances
| Instance Name | Cplex | Gurobi | AutoRoster | ScheduleNurse3 |
|---|---|---|---|---|
| Instance4 | 4.4/0.6=7.3 | 4/0.6=6.7 | 6/0.6=10 | 0.6/0.6=1 |
| Instance5 | 29/2.4=12.1 | 16/2.4=6.7 | - | 2.4/2.4=1 |
| Instance6 | 7/1.6=4.4 | 5/1.6=3.1 | - | 1.6/1.6=1 |
| Instance7 | 61/6.2=9.8 | 20/6.2=3.2 | - | 6.2/6.2=1 |
| Instance8 | 4623/50=92.5 | 931/50=18.6 | - | 50/50=1 |
| Instance9 | - | - | - | - |
| Instance10 | 41/13=3.2 | 20/13=1.5 | 660/13=50.8 | 13/13=1 |
| Instance11 | 45/18=2.5 | 18/18=1 | 71/18=3.9 | 37/18=2.1 |
| Instance12 | 260/54=4.8 | 185/54=3.4 | 660/54=12.2 | 54/54=1 |
| Instance13 | - | 12115/572=21.2 | - | 572/572=1 |
| Instance14 | 690/4.3=160.5 | 205/4.3=47.7 | - | 4.3/4.3=1 |
| Instance15 | - | - | - | - |
| Instance16 | 937/4.3=217.9 | 78/4.3=18.1 | - | 4.3/4.3=1 |
| Instance17 | 4022/4.8=837.9 | 143/4.8=29.8 | 10000/4.8=2083.3 | 4.8/4.8=1 |
| Instance18 | 21387/135=158.4 | 787/135=5.8 | - | 135/135=1 |
| Instance19 | - | 3006/3006=1 | - | 5285/3006=1.8 |
| Instance20 | - | 3665/678=5.4 | - | 678/678=1 |
Optimal Objective Reached Instances
|
| Instance Name | Cplex | Gurobi | AutoRoster | ScheduleNurse3 |
|---|---|---|---|---|
| Instance4 | 4.4/0.5=8.8 | 4/0.5=8 | 6/0.5=12 | 0.5/0.5=1 |
| Instance5 | 29/2.4=12.1 | 16/2.4=6.7 | 11/2.4=4.6 | 2.4/2.4=1 |
| Instance6 | 7/1.6=4.4 | 5/1.6=3.1 | - | 1.6/1.6=1 |
| Instance7 | 61/6.2=9.8 | 20/6.2=3.2 | - | 6.2/6.2=1 |
| Instance8 | 4623/50=92.5 | 931/50=18.6 | - | 50/50=1 |
| Instance9 | - | - | - | - |
| Instance10 | 41/13=3.2 | 20/13=1.5 | 660/13=50.8 | 13/13=1 |
| Instance11 | 45/18=2.5 | 18/18=1 | 71/18=3.9 | 37/18=2.1 |
| Instance12 | 260/54=4.8 | 185/54=3.4 | 660/54=12.2 | 54/54=1 |
| Instance13 | - | 12115/572=21.2 | - | 572/572=1 |
| Instance14 | 690/4.3=160.5 | 205/4.3=47.7 | - | 4.3/4.3=1 |
| Instance15 | - | - | - | - |
| Instance16 | 937/4.3=217.9 | 78/4.3=18.1 | - | 4.3/4.3=1 |
| Instance17 | 4022/4.8=837.9 | 143/4.8=29.8 | 10000/4.8=2083.3 | 4.8/4.8=1 |
| Instance18 | 21387/135=158.4 | 787/135=5.8 | - | 135/135=1 |
| Instance19 | - | 3006/3006=1 | - | 5285/3006=1.8 |
| Instance20 | - | 3665/678=5.4 | - | 678/678=1 |
Time - Number of Instances proven optimality
Time - Number of Instances reached optimal objective
Detail Data
