Tightening methods for continuous-time mixed-integer programming models for chemical production scheduling

Andres F. Merchan, Sara Velez, Christos T. Maravelias

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Significance: Important advances in modeling chemical production scheduling problems have been made in recent years, yet effective solution methods are still required. We use an algorithm that uses process network and customer demand information to formulate powerful valid inequalities that substantially improve the solution process. In particular, we extend the ideas recently developed for discrete-time formulations to continuous-time models and show that these tightening methods lead to a significant decrease in computational time, up to more than three orders of magnitude for some instances.

Original languageEnglish (US)
Pages (from-to)4461-4467
Number of pages7
JournalAIChE Journal
Volume59
Issue number12
DOIs
StatePublished - Dec 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Environmental Engineering
  • Chemical Engineering(all)

Keywords

  • Demand propagation
  • Mixed-integer programming
  • Valid inequalities

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