Abstract
Staffing across multiple time periods with uneven demand is a common problem in many organizations. There are many models for optimal cyclic personnel scheduling, but none of these incorporates the optimal number-of-workers problem or the optimal staff-skills-composition problem. In this paper, we introduce a variation on cyclic scheduling that incorporates discrete-event simulation and specialized data collection for a staffing plan as part of a general methodology. The result is a four-step approach based on a stochastic optimization model for scheduling and staffing an organization. We illustrate this approach with a semiconductor manufacturing case study.
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