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In this paper, we propose a new approach for solving the air traffic controller (ATC) work shift scheduling problem, which minimizes the number of ATCs required to cover a given airspace sectoring, while satisfying a set of ATC labor conditions. This optimization problem belongs to the class of timetabling problems. The size and complexity of these combinatorial problems make them hard or even impossible to solve with exact methods. In the proposed approach, initial feasible solutions are first built using a heuristic based on optimized templates, and then multistart simulated annealing is used to reach optimal solutions. In the search process, we use regular expressions to check the feasibility of the generated solutions. This provides high testing speed and modularity for a clear and maintainable implementation of the optimization model. Once the optimal ATC number is reached in one or more solutions, they are used as the initial solutions for a new optimization process aimed at balancing the ATC workloads. The proposed approach is illustrated using a real example, and the optimal solution reached outperforms the reference solution, i.e. a real solution derived from the currently used tools based on templates. Indeed, one less ATC is needed to cover the airspace sectoring, and the ATC workloads are more balanced.