Stochastic programming approaches for staffing in call centers with uncertain forecasts

Call centers are essential infrastructures but loom large in a company budget. An important way to reduce costs is the staffing optimization: how many agents should be hired to minimize costs without penalizing the expected Quality of Service? We model a call-center after a queueing system and consider the distribution of arrival times as a computed forecast subjected to uncertainty. We chose a stochastic programming approach to propose a staffing solution, first with a disjoint chance-constraint formulation and then with a joint chance-constraint formulation. Preliminary results are given