Mixed-Integer Fractional Programming: Models, Algorithms, and Applications in Process Operations, Energy Systems, and Sustainability

Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

A wide range of optimization problems arising in practical applications can be formulated as mixed-integer fractional programming (MIFP) problems, which combine the combinatorial difficulty of optimizing over discrete variable sets with the challenges of handling the nonconvex fractional objective function. This paper reviews recent developments of tailored global optimization algorithms for large-scale MIFP problems. These MIFP methods are illustrated through three applications: (1) function-unit-based life cycle optimization of sustainable supply chains, (2) integrated optimization of production scheduling and process dynamics of multi-product continuous processes, and (3) optimal design of algae processes for fuel and chemical production.

Original languageEnglish (US)
Pages (from-to)109-116
Number of pages8
JournalComputer Aided Chemical Engineering
Volume37
DOIs
StatePublished - Jan 1 2015

Keywords

  • Algorithm
  • Biorefinery
  • Life cycle optimization
  • MINLP
  • Scheduling

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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