Abstract
Production scheduling faces three challenges, which are inconsistent key performance indicators (KPIs), processing time uncertainties, and production schemes. Applying modern portfolio theory (MPT), Li et al. (2021) proposed a ToB(α) heuristic to balance trade-offs in one-stage production. However, production schemes for optimizing average performance of individual KPIs, trade-off values, or worst-case scenarios affect the stability of a process differently, especially with processing time uncertainties. We propose an innovative approach using transfer functions for stability (TF4S) in balancing trade-offs in production scheduling. Our TF4S approach provides a systematic way to analyze the stability of one-stage production and can be extended to production scheduling for classic m-machine flow lines.
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