Applying Quantum Annealing for Shift Scheduling Problem for Call Centers

Abstract

Quantum annealing (QA) has shown good solutions quickly in benchmarks of combinatorial optimization problems. There are not many real-world problems that illustrate the effectiveness of QA compared to the typical optimization methods. We applied QA to a shift scheduling problem for call centers with four conditions. The shift scheduling problem for call centers optimizes shifts for a specific period of time while satisfying various constraints, such as satisfying the desired worker's shifts. In this paper, we formulated the shift scheduling problem for call centers in QUBO to apply QA. We tuned various parameters required to execute the QA. Then, we compared QA with six typical optimization methods using a classical computer to investigate QA's effectiveness for the shift scheduling problem for call centers. The results show that for three instances with up to 126 variables, QA is about 3-14 times faster than other methods and obtains enough quality of solutions. This shows that QA can be one of the effective methods to solve practical applications in the real-world.