A Two-stage Model for Multi-task Call Center Shift Scheduling

An effective scheduling system can significantly reduce the waste of human and material resources, making the operation of an enterprise more efficient and bringing great convenience to customers. This study investigates the multi-task daily shift scheduling problem for call centers. Traditional set covering models are widely used to address such problems, but in practice, the increase in model computation time explodes due to growth in task patterns and the accompanying size increases. Consequently, these models may not be solvable within reasonable time. In our previous study, an implicit modeling approach was employed to maximize the processing volume. However, the tasks might vary more frequently than necessary. In this study, this problem is addressed by introducing a two-stage optimization model to obtain the optimal solution that ensures that staff do not change tasks frequently.