Employee scheduling with SAT-based pseudo-boolean constraint solving
The aim of this paper is practical: to show that, for at least one important real-world problem, modern SAT-based technology can beat the extremely mature branch-and-cut solving methods implemented in well-known state-of-the-art commercial solvers such as CPLEX or Gurobi. The problem of employee sch...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/355638 |
| Acceso en línea: | https://hdl.handle.net/2117/355638 https://dx.doi.org/10.1109/ACCESS.2021.3120597 |
| Access Level: | acceso abierto |
| Palabra clave: | Production planning Production scheduling Employee scheduling 0-1 integer linear program Propositional satisfiability Producció -- Planificació Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica |
| Sumario: | The aim of this paper is practical: to show that, for at least one important real-world problem, modern SAT-based technology can beat the extremely mature branch-and-cut solving methods implemented in well-known state-of-the-art commercial solvers such as CPLEX or Gurobi. The problem of employee scheduling consists in assigning a work schedule to each of the employees of an organization, in such a way that demands are met, legal and contractual constraints are respected, and staff preferences are taken into account. This problem is typically handled by first modeling it as a 0-1 integer linear program (ILP). Our experimental setup considers as a case study the 0-1 ILPs obtained from the staff scheduling of a real-world car rental company, and carefully compares the performance of CPLEX and Gurobi with our own simple conflict-driven constraint-learning pseudo-Boolean solver. |
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