Hybrid model predictive control applied to production-inventory systems

Naresh N. Nandola, Daniel Rivera

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


Hybrid production-inventory systems are characterized by discrete decisions on production levels and/or capacity. These systems have broad applicability to important, emerging applications of process control concepts, among them time-varying adaptive behavioral interventions and supply chain management. This paper examines the usefulness of hybrid model predictive control (HMPC) in these two novel application settings. In a hypothetical adaptive behavioral intervention inspired by Fast Track (a preventive intervention for reducing conduct disorder in at-risk children), HMPC is presented as a means to improve the assignment of frequency of home-based counseling visits to families with low parental function. In supply chain management, the usefulness of HMPC for assigning production capacity in an inventory control problem under conditions of varying customer demand is presented. These problems are modeled as mixed logical dynamical (MLD) systems, with HMPC consisting of a Mixed Integer Quadratic Program (MIQP) that employs a three-degree-of-freedom parametrization for achieving ease of tuning and facilitating robust performance under uncertainty.

Original languageEnglish (US)
Title of host publicationProceedings of the 18th IFAC World Congress
PublisherIFAC Secretariat
Number of pages6
Edition1 PART 1
ISBN (Print)9783902661937
StatePublished - 2011

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1 PART 1
ISSN (Print)1474-6670


  • Adaptive behavioral interventions
  • Hybrid systems
  • Model Predictive Control
  • Production-inventory systems
  • Supply chain management

ASJC Scopus subject areas

  • Control and Systems Engineering


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