Bi-objective reentrant hybrid flowshop scheduling: An iterated Pareto greedy algorithm

Kuo Ching Ying, Shih Wei Lin*, Shu Yen Wan

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

62 Scopus citations

Abstract

The multi-objective reentrant hybrid flowshop scheduling problem (RHFSP) exhibits significance in many industrial applications, but appears under-studied in the literature. In this study, an iterated Pareto greedy (IPG) algorithm is proposed to solve a RHFSP with the bi-objective of minimising makespan and total tardiness. The performance of the proposed IPG algorithm is evaluated by comparing its solutions to existing meta-heuristic algorithms on the same benchmark problem set. Experimental results show that the proposed IPG algorithm significantly outperforms the best available algorithms in terms of the convergence to optimal solutions, the diversity of solutions and the dominance of solutions. The statistical analysis manifestly shows that the proposed IPG algorithm can serve as a new benchmark approach for future research on this extremely challenging scheduling problem.

Original languageEnglish
Pages (from-to)5735-5747
Number of pages13
JournalInternational Journal of Production Research
Volume52
Issue number19
DOIs
StatePublished - 2014

Keywords

  • bi-objective
  • meta-heuristic
  • reentrant hybrid flowshop
  • scheduling

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