This paper investigates an integrated production planning and cutting stock problem that is common in small-scale furniture plants, in which the production costs involved in the manufacturing process and the demands for the products are not known precisely. To deal with these uncertainties, robust optimization models that control the conservatism of the solution according to the attitude of the decision maker towards risk were proposed. Computational experiments based on real data from a furniture plant showed that it is possible to obtain robust solutions without overly sacrificing the total cost. In addition, it was observed that commonly used strategies to deal with uncertainty issues can result in production plans with prohibitive total costs.
Production planning; Furniture plants; Uncertain costs; Uncertain demands; Robust optimization
