Minimizing total completion time in the no-wait jobshop scheduling problem using a backtracking metaheuristic

Kuo Ching Ying, Shih Wei Lin*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

15 Scopus citations

Abstract

This study focused on the no-wait jobshop scheduling problem (NWJSP), which is NP-hard in the strong sense. A new benchmarking algorithm, named backtracking multi-start simulated annealing (BMSA), is presented in this study for minimizing the total completion time in NWJSPs. To effectively and efficiently find (near-) optimal schedules, the simulated annealing algorithm is strengthened by integrating the multi-start and backtracking mechanisms that enable the search processes to escape from the local optimum. The performance of the BMSA algorithm is assessed by comparing its experimental results to those of the best available metaheuristics on three well-known benchmark problem sets. Computational results and statistical analyses confirm that the BMSA algorithm significantly outperforms these benchmark metaheuristics. This study mainly contributes to providing an innovative approach for solving this highly intractable scheduling problem, which is also worth applying to solve a practical NWJSP.

Original languageEnglish
Article number108238
JournalComputers and Industrial Engineering
Volume169
DOIs
StatePublished - 07 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Metaheuristics
  • No-wait jobshop
  • Scheduling
  • Total completion time

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