Model predictive scheduling of semi-cyclic discrete-event systems using switching max-plus linear models and dynamic graphs

Ton J.J. van den Boom*, Marenne van den Muijsenberg, Bart De Schutter

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
40 Downloads (Pure)

Abstract

In this paper we discuss scheduling of semi-cyclic discrete-event systems, for which the set of operations may vary over a limited set of possible sequences of operations. We introduce a unified modeling framework in which different types of semi-cyclic discrete-event systems can be described by switching max-plus linear (SMPL) models. We use a dynamic graph to visualize the evolution of an SMPL system over a certain period in a graphical way and to describe the order relations of the system events. We show that the dynamic graph can be used to analyse the structural properties of the system. In general the model predictive scheduling design problem for SMPL systems can be recast as a mixed integer linear programming (MILP) problem. In order to reduce the number of optimization parameters we introduce a novel reparametrization of the MILP problem. This may lead to a decrease in computational complexity.

Original languageEnglish
Pages (from-to)635-669
JournalDiscrete Event Dynamic Systems: theory and applications
Volume30
Issue number4
DOIs
Publication statusPublished - 2020

Keywords

  • Mixed integer linear programming
  • Model predictive scheduling
  • Switching max-plus linear systems

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