Trade-off balancing in one-stage production with processing times uncertainties

Inconsistencies between key performance indicators (KPIs) and processing time uncertainties (PTUs) are two fundamental challenges to operations management in one-stage scheduling. Robust scheduling for the worst-case scenarios is recommended to hedge against PTU over optimal scheduling. Modern portfolio theory can be used to balance trade-offs between inconsistent KPIs, in terms of the expected cost E and variance σ2. We raise two research questions for trade-off balancing with PTU in one-stage scheduling. The first question (Q1) is whether an optimal scheduling method generates a solution better than a robust scheduling method, in terms of smaller average and maximum deviations from optimal solutions for individual KPIs, and the second one (Q2) is whether the suitable scheduling method generates a different solution space for efficiency in terms of E and σ. Revising trade-off balancing [ToB (α)] heuristics for optimal scheduling and comparing them with the end-point product (EP) and end-point sum (ES) heuristics for robust scheduling, we conclude that our revised ToB (α) heuristics are more robust to PTU and provide a different solution space of trade-off balancing for the efficiency.