Abstract
The rotating workforce scheduling problem aims to schedule workers satisfying shift sequence constraints and ensuring enough shifts are covered on each day, where every worker completes the same schedule, just starting at different days in the schedule. We give two solver independent models for the rotating workforce scheduling problem and compare them using different solving technology, both constraint programming and mixed integer programming. We show that the best of these models outperforms the state-of-the-art for the rotating workforce scheduling problem, and that solver independent modeling allows us to use different solvers to achieve different aims: e.g., speed to solution or robustness of solving (particular for unsatisfiable problems). We give the first complete method able to solve all of the standard benchmarks for this problem.
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- 1.
Available at http://www.dbai.tuwien.ac.at/staff/musliu/benchmarks/.
- 2.
We also tried Gecode as a constraint programming solver, but it was not competitive.
- 3.
We ran preliminary experiments on all possible combinations with a five minutes runtime limit.
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Acknowledgments
This work was partially supported by the Asian Office of Aerospace Research and Development grant 15-4016 and by the Austrian Science Fund (FWF): P24814-N23.
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Musliu, N., Schutt, A., Stuckey, P.J. (2018). Solver Independent Rotating Workforce Scheduling. In: van Hoeve, WJ. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2018. Lecture Notes in Computer Science(), vol 10848. Springer, Cham. https://doi.org/10.1007/978-3-319-93031-2_31
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