New Scheduling Algorithms and Digital Tool for Dynamic Permutation Flowshop with Newly Arrived Order

Weibo Liu, Yan Jin, Mark Price

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
286 Downloads (Pure)

Abstract

The permutation flowshop scheduling problem has been widely studied under static environment by assuming machines and jobs are available at the time of zero. However, in reality, new orders arrive at production systems randomly, which leads to sheer complexity in scheduling due to the dynamic changes given various constraints of resources. Previous studies simply attach new orders directly after the existing schedule. Recent study by Perez-Gonzalez and Framinan (2015) shows mixing jobs of old and new orders could result in better scheduling solutions. But the heuristic algorithms are still lacking to implement the job mixing policy. To address this problem, a novel scheduling strategy is herein proposed by integrating match-up strategy and real-time strategy (MR) in order to make use of the remaining time before the old order due date. Based on the new MR strategy, eleven new heuristics are introduced with ten existing and one new priority rules. Computational results illustrate the effectiveness of the new heuristics. A digital tool is developed for ease of application of these heuristics, and it is validated by case studies.
Original languageEnglish
Pages (from-to)3234-3248
Number of pages15
JournalInternational Journal of Production Research
Volume55
Issue number11
Early online date06 Feb 2017
DOIs
Publication statusPublished - 2017

Keywords

  • Heuristics
  • Dynamic scheduling
  • New order
  • Permutation flowshop
  • Order mixing

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