Performance analysis and capacity planning for stochastic systems with cut-off service levels

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The research project described in the renewal proposal is intended to investigate the influence of different cut-off service level definitions on capacity planning, in particular on workforce requirement planning and shift scheduling. These service level definitions are commonly used in industry. They define a cut-off time and a deadline by which all orders received by the cut-off time have to be completely processed. The structural differences in the definition of a cut-off service level compared to traditional service levels prevents the transfer of insights with regard to optimal capacities. Therefore, new methods for capacity planning have to be developed. The overall objective is therefore to identify and explain the influences of system parameters, e.g. the processing capacity available, on the achievable cut-off service level. This enables insights into the effects of cut-off service levels on workforce requirements and shift scheduling. For this purpose, performance analysis methods for stochastic, time-dependent, single-stage and multi-stage systems are to be developed. Discrete-time queueing networks will be used for the performance analysis. For appropriate special cases, structural insights are to be derived analytically. They are derived for deterministic surrogate models and single-period stochastic models. We develop new approaches for workforce requirement planning and shift scheduling by using a cut-off service level. The structural findings gained before will serve as bounds in the solution approaches. The single stage results will then be extended to multi-level systems, based on the results of the current project.