Towards control-relevant forecasting in supply chain management

Jay D. Schwartz, Daniel Rivera, Karl G. Kempf

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


The focus of this paper is understanding the effects of demand forecast error on a tactical decision policy for a single node of a manufacturing supply chain. The demand forecast is treated as an external measured disturbance in a multi-degree-of-freedom feedback-feedforward Internal Model Control (IMC) based inventory control system. Because forecast error will be multifrequency in nature, the effect of error in different frequency regimes is examined. A mathematical framework for evaluating the effect of forecast revisions in an IMC controller is developed. A Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm is implemented to develop an optimal tuning strategy under these conditions. For the IMC-based inventory controller presented it is concluded that the most desirable performance may be obtained by acting cautiously (e.g. implementing small changes to factory starts) to initial forecasts and gradually becoming more aggressive on starts until the actual demand change is realized.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Number of pages6
StatePublished - 2005
Event2005 American Control Conference, ACC - Portland, OR, United States
Duration: Jun 8 2005Jun 10 2005


Other2005 American Control Conference, ACC
Country/TerritoryUnited States
CityPortland, OR

ASJC Scopus subject areas

  • Control and Systems Engineering


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