Tactical supply chain planning under uncertainty with an application in the wind turbines industry

Abstract

With today's rapidly changing global market place, it is essential to explicitly include uncertainty in supply chain planning models. In this paper, we develop a two-stage stochastic programming model for the comprehensive tactical planning of supply chains under demand and supply uncertainty. The model handles multi-period, multi-product, and multi-echelon supply chains. It incorporates backorder penalties with general cost structures. The considered supply uncertainty combines supplier random yield and stochastic lead times, and is thus the most general form of such uncertainty to date. We illustrate how our model directly applies to the planning of the supply chain of one of the world's biggest manufacturers of wind turbines. We illustrate theoretical and numerical results that show the impact of supplier uncertainty/unreliability on optimal procurement decisions. We also quantify the value of modeling uncertainty versus deterministic planning.