On discrete time chemical production scheduling MILP models containing record keeping variables

Amin Samadi, Nathan Adelgren, Christos T. Maravelias

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper, we present strategies for reformulating discrete time-based mixed-integer programming models for chemical production scheduling. We introduce several new integer variables, which we refer to as record keeping variables, that mixed-integer linear programming solvers are able to exploit in order to reduce total solution time. We consider these record keeping variables in the context of both batch process networks and continuous process networks. Results of several computational tests are provided that demonstrate the utility of incorporating record keeping variables in chemical production scheduling models.

Original languageEnglish (US)
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier B.V.
Pages433-438
Number of pages6
DOIs
StatePublished - Jan 2023

Publication series

NameComputer Aided Chemical Engineering
Volume52
ISSN (Print)1570-7946

All Science Journal Classification (ASJC) codes

  • General Chemical Engineering
  • Computer Science Applications

Keywords

  • batch process
  • continuous process
  • discrete time
  • reformulation
  • scheduling

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