Discrete-time mixed-integer programming models and solution methods for production scheduling in multistage facilities

Andres F. Merchan, Hojae Lee, Christos T. Maravelias

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

We address the problem of production scheduling in multi-product multi-stage batch plants. Unlike most of the previous works, which propose continuous-time models, we study discrete-time mixed-integer programming models and solution methods. Specifically, we discuss two models based on network representations of the facility and develop two new models inspired by the Resource-Constrained Project Scheduling Problem. Furthermore, we propose different solution methods, including tightening methods based on processing unit availability, a reformulation based on processing unit occupancy, and an algorithm to refine approximate solutions for large-scale instances. Finally, we present a comprehensive computational study which shows that speedups of up to four orders of magnitude in are observed when our models and methods are compared to existing approaches.

Original languageEnglish (US)
Pages (from-to)387-410
Number of pages24
JournalComputers and Chemical Engineering
Volume94
DOIs
StatePublished - Nov 2 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications

Keywords

  • Reformulations
  • Resource-constrained project scheduling
  • Sequential production environments
  • Tightening constraints

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