This paper develops methods to determine appropriate staffing levels in call centers and other many-server queueing systems with time-varying arrival rates. The goal is to achieve targeted time-stable performance, even in the presence of significant time-variation in the arrival rates. The main contribution is a flexible simulation-based iterative-staffing algorithm (ISA) for the Mt/G/st + G model- with nonhomogeneous Poisson arrival process (the Mt) and customer abandonment (the +G). For Markovian Mt/M/st + M special cases, the ISA is shown to converge. For that Mt/M/st+M model, simulation experiments show that the ISA yields time-stable delay probabilities across a wide range of target delay probabilities. With ISA, other performance measures- such as agent utilizations, abandonment probabilities and average waiting times- are stable as well. The ISA staffing and performance agree closely with the modified-offered-load (MOL) approximation, which was previously shown to be an effective staffing algorithm without customer abandonment. While the ISA algorithm so far has only been extensively tested for Mt/M/st + M models, it can be applied much more generally, to Mt/G/st + G models and beyond
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