robust simultaneous lot-sizing & scheduling model with uncertain demand

optimization models have been used to support decision making in production planning for a long time. however, several of those models are deterministic and do not address the variability that is present in some of the data. robust optimization is a methodology which can deal with the uncertainty or variability in optimization problems by computing a solution which is feasible for all possible scenarios of the data within a given uncertainty set. simultaneous lot-sizing & scheduling is an important problem in production planning environments. in this paper, we consider a simultaneous lot-sizing & scheduling problem with uncertain demand. a robust optimization criterion considering to deviation from optimal and shortage cost is applied to formulate a robust linear programming model. finally, we provide a set of numerical examples to verify the effectiveness of the approach. a fix & relax algorithm used to solve the problem. experimental result shows that the solving problem algorithm in lower time.