On decomposition and multiobjective-based column and disjunctive cut generation for MINLP

P. Muts, Iwo Nowak*, E.M.T. Hendrix

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

Most industrial optimization problems are sparse and can be formulated as block-separable mixed-integer nonlinear programming (MINLP) problems, defined by linking low-dimensional sub-problems by (linear) coupling constraints. This paper investigates the potential of using decomposition and a novel multiobjective-based column and cut generation approach for solving nonconvex block-separable MINLPs, based on the so-called resource-constrained reformulation. Based on this approach, two decomposition-based inner- and outer-refinement algorithms are presented and preliminary numerical results with nonconvex MINLP instances are reported.
Original languageEnglish
Pages (from-to)1389-1418
JournalOptimization and Engineering
Volume22
Issue number3
Early online date11 Nov 2020
DOIs
Publication statusPublished - 2021

Keywords

  • Column generation
  • Decomposition method
  • Global optimization
  • Mixed-integer nonlinear programming
  • Nonconvex optimization
  • Parallel computing

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