Robust Optimization Model for Inventory Control Problems Production Raw Materials With Storage Costs and Orders Under Uncertainty

Inventory is a major part of a company's operations which can have a negative impact if it was not managed properly. Inventory control must be planned and controlled effectively and efficiently. The main problem in inventory control usually occurs because there are parameters that contain data uncertainty, such as uncertain product demand. Because of this element of uncertainty, it definitely influenced decision makers, according to many studies have discussed how to control uncertainty or minimize its impact. Therefore, This research presented a robust optimization model that can overcome the element of uncertainty in controlling the inventory of production raw materials, namely the uncertainty in the amount of demand for production raw materials where ordering capacity can only be ordered at the maximum value to obtain an optimal solution. Completion of the model was done by changing the mixed integer programming (MIP) problem into a linear programming (LP) problem. Data simulation was carried out with the help of MATLAB to obtain optimal results from the model created. This research also provides indications for decision makers in a company to model and control the company's production raw materials if demand becomes uncertain. Completion of the model was done by changing the mixed integer programming (MIP) problem into a linear programming (LP) problem. Data simulation was carried out with the help of MATLAB to obtain optimal results from the model created. This research also provides indications for decision makers in a company to model and control the company's production raw materials if demand becomes uncertain. Completion of the model was done by changing the mixed integer programming (MIP) problem into a linear programming (LP) problem. Data simulation was carried out with the help of MATLAB to obtain optimal results from the model created. This research also provides indications for decision makers in a company to model and control the company's production raw materials if demand becomes uncertain.