• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Journal articles
    • View Item
    • Home
    • Griffith Research Online
    • Journal articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • Scheduling blocking flowshops with setup times via constraint guided and accelerated local search

    Thumbnail
    View/Open
    Newton222175.pdf (933.6Kb)
    File version
    Accepted Manuscript (AM)
    Author(s)
    Newton, MA Hakim
    Riahi, Vahid
    Su, Kaile
    Sattar, Abdul
    Griffith University Author(s)
    Sattar, Abdul
    Su, Kaile
    Year published
    2019
    Metadata
    Show full item record
    Abstract
    Permutation flowshop scheduling problem (PFSP) is a classical NP-Hard combinatorial optimisation problem. Existing PFSP variants capture different realistic scenarios, but significant modelling gaps still remain with respect to many real-world industrial applications. Inspired by the cider industry, in this paper, we propose a new PFSP variant that generalises over simultaneous use of several types of blocking constraints and various settings of sequence-dependent setup times. We also present a computational model for makespan minimisation of the new variant and show that solving this variant remains NP-Hard. For this PFSP ...
    View more >
    Permutation flowshop scheduling problem (PFSP) is a classical NP-Hard combinatorial optimisation problem. Existing PFSP variants capture different realistic scenarios, but significant modelling gaps still remain with respect to many real-world industrial applications. Inspired by the cider industry, in this paper, we propose a new PFSP variant that generalises over simultaneous use of several types of blocking constraints and various settings of sequence-dependent setup times. We also present a computational model for makespan minimisation of the new variant and show that solving this variant remains NP-Hard. For this PFSP variant, we then present an acceleration method to compute makespan efficiently and thus evaluate the neighbourhoods generated by insertion operators. We develop a new constructive heuristic taking both blocking constraints and setup times into account. We also develop a new local search algorithm that uses a constraint guided intensification method and a random-path guided diversification method. Our comprehensive experimental results on a set of benchmark instances demonstrate that our proposed algorithms significantly outperform several state-of-the-art adapted algorithms.
    View less >
    Journal Title
    COMPUTERS & OPERATIONS RESEARCH
    Volume
    109
    DOI
    https://doi.org/10.1016/j.cor.2019.04.024
    Copyright Statement
    © 2019 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Subject
    Applied mathematics
    Numerical and computational mathematics
    Publication URI
    http://hdl.handle.net/10072/385068
    Collection
    • Journal articles

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E
    • TEQSA: PRV12076

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander