Control-relevant estimation of demand models for closed-loop control of a production-inventory system

The development of control-oriented decision policies for inventory management in supply chains has received considerable interest in recent years, and demand modeling to supply forecasts for these policies is an important component of an effective solution to this problem. Drawing from the problem of control-relevant parameter estimation, this paper presents an approach for demand modeling in a production-inventory system that relies on a control-relevant weight to tailor the emphasis of the fit to the intended purpose of the model, which is to provide forecast signals tactical inventory management policies based on internal model control. The formulation is multi-objective in nature, allowing the user to emphasize inventory variation, starts change variation, or a weighted combination. By integrating the demand modeling and inventory control problems, it is possible to obtain reduced-order demand models that exhibit superior performance. A systematic approach for generating these weights is presented and the benefits resulting from their use demonstrated on a representative production-inventory system case study.