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 . problem employee scheduling consists assigning a work schedule each employees an organization, way that demands are met, legal and contractual constraints respected, staff preferences taken into account. This typically handled by first modeling it 0–1 integer linear program (ILP). Our experimental setup considers case study ILPs obtained from car rental company, carefully compares performance with our own simple conflict-driven constraint-learning pseudo-Boolean solver.