A model predictive control framework for robust management of multi-product, multi-echelon demand networks

M. W. Braun, Daniel Rivera, W. M. Carlyle, K. G. Kempf

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

3 Scopus citations

Abstract

Model Predictive Control (MPC) is presented as a robust, flexible decision framework for dynamically managing inventories and meeting customer demand in demand networks (a.k.a. supply chains). Ultimately, required safety stock levels in demand networks can be significantly reduced as a result of the performance demonstrated by the MPC approach. The translation of available information in the supply chain problem into MPC variables is demonstrated with a two-node supply chain example. A six-node, two-product, three-echelon demand network problem proposed by Intel is well managed by a partially decentralized MPC implementation under simultaneous demand forecast inaccuracies and plant-model mismatch.

Original languageEnglish (US)
Title of host publicationIFAC Proceedings Volumes (IFAC-PapersOnline)
PublisherIFAC Secretariat
Pages23-28
Number of pages6
Volume15
Edition1
Publication statusPublished - 2002
Event15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
Duration: Jul 21 2002Jul 26 2002

Other

Other15th World Congress of the International Federation of Automatic Control, 2002
CountrySpain
CityBarcelona
Period7/21/027/26/02

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Keywords

  • Inventory control
  • Model predictive control
  • Supply chain management

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Braun, M. W., Rivera, D., Carlyle, W. M., & Kempf, K. G. (2002). A model predictive control framework for robust management of multi-product, multi-echelon demand networks. In IFAC Proceedings Volumes (IFAC-PapersOnline) (1 ed., Vol. 15, pp. 23-28). IFAC Secretariat.