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.