Uniform workload assignments for assembly line by GA-based amelioration approach

Reakook Hwang, Hiroshi Katayama

    Research output: Contribution to journalArticle

    11 Citations (Scopus)

    Abstract

    This paper presents an amelioration structure with genetic algorithms to improve the variation of workload on assembly line production systems. As a consequence of introducing the just-in-time (JIT) production principle, it has been recognised that U-shaped assembly line systems offer several benefits over the traditional straight line systems. We consider both the traditional straight line system and the U-shaped assembly line system, thus as an unbiased examination of line efficiency. The performance criteria considered are the number of workstations (the line efficiency) and the variation of workload. The results of experiments show that the proposed an amelioration structure produced optimal line efficiency of workstation integration and improved the variation of workload.

    Original languageEnglish
    Pages (from-to)1857-1871
    Number of pages15
    JournalInternational Journal of Production Research
    Volume48
    Issue number7
    DOIs
    Publication statusPublished - 2010 Jan

    Fingerprint

    Just in time production
    Genetic algorithms
    Assembly line
    Gas
    Assignment
    Workload
    Experiments
    Just-in-time production
    Genetic algorithm
    Experiment
    Performance criteria

    Keywords

    • Genetic algorithm
    • Priority-based coding
    • U-shaped assembly line

    ASJC Scopus subject areas

    • Industrial and Manufacturing Engineering
    • Management Science and Operations Research
    • Strategy and Management

    Cite this

    Uniform workload assignments for assembly line by GA-based amelioration approach. / Hwang, Reakook; Katayama, Hiroshi.

    In: International Journal of Production Research, Vol. 48, No. 7, 01.2010, p. 1857-1871.

    Research output: Contribution to journalArticle

    Hwang, Reakook ; Katayama, Hiroshi. / Uniform workload assignments for assembly line by GA-based amelioration approach. In: International Journal of Production Research. 2010 ; Vol. 48, No. 7. pp. 1857-1871.
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