Robust optimization for tactical capacity planning in ETO industry subject to uncertain costs

In Engineer-to-Order (ETO) context, cost uncertainty plays a major role as prices must be defined during at the early stages of project development. Notwithstanding, there is a research-practice gap on the application of decision support tools that incorporate information about uncertainty within ETO planning. To address this gap, this paper extends a previous action research relative to an ETO industrial situation where a robust optimization model considering process uncertainties was applied. The contribution given now refers to an adaptation of this model considering cost uncertainties. A sensitivity analysis was employed to identify the key drivers of variability of the optimal cost. A robust model was reformulated to incorporate the variability relative to the most relevant parameters. A numerical example was applied revealing the effects of the conservatism level on the optimal solution. The insights gained from this application may stimulate academics and practitioners to investigate news issues regarding this area.