Optimal Control of Integrated Production – Forecasting System

In this work, optimal control theory is used to derive the optimal production rate in a manu‐ facturing system presenting the following features: the demand rate during a certain period depends on the demand rate of the previous period (dependent demand), the demand rate depends on the inventory level, items in inventory are subject to deterioration, and the firm can adopt a periodic or a continuous review policy. Also, we are using the fact that the cur‐ rent demand is related to the previous demand in order to integrate the forecasting compo‐ nent into the production planning problem. The forecast of future demand for the products being produced is needed to plan future activities. Forecasting information is an important input in several areas of manufacturing activity. This problem has been considered in the literature. The proposed approach is different from that of other authors which is mainly based on time-series. In [1], the authors deal with the interaction between forecasting and stock control in the case of non-stationary demand. In [2], the authors assume a distribution for the unknown demand, estimate its parameters and replace the unknown demand pa‐ rameters by these estimates in the theoretically correct model. In [3], the authors propose an approach to evaluate the impact of interaction between demand forecasting method and stock control policy on the inventory system performances. In [4], the authors present a sup‐ ply chain management framework based on model predictive control (MPC) and time series forecasting. In [5], the authors consider a data-driven forecasting technique with integrated inventory control for seasonal data and compare it to the traditional Holt-Winters algorithm