Sustainable scheduling of batch processes under economic and environmental criteria with MINLP models and algorithms

Dajun Yue, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

60 Scopus citations

Abstract

We address the bi-criterion optimization of batch scheduling problems with economic and environmental concerns. The economic objective is expressed in terms of productivity, which is the profit rate with respect to the makespan. The environmental objective is evaluated by means of environmental impact per functional unit based on the life cycle assessment methodology. The bi-criterion optimization model is solved with the ε-constraint method. Each instance is formulated as a mixed-integer linear fractional program (MILFP), which is a special class of non-convex mixed-integer nonlinear programs. In order to globally optimize the resulting MILFPs effectively, we employ the tailored reformulation-linearization method and Dinkelbach's algorithm. The optimal solutions lead to a Pareto frontier that reveals the tradeoff between productivity and environmental impact per functional unit. To illustrate the application, we present two case studies on the short-term scheduling of multiproduct and multipurpose batch plants.

Original languageEnglish (US)
Pages (from-to)44-59
Number of pages16
JournalComputers and Chemical Engineering
Volume54
DOIs
StatePublished - Jul 11 2013

Keywords

  • Batch manufacturing
  • Global optimization
  • LCA
  • Multiobjective optimization
  • Process operations
  • Sustainability

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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