Operation planning based on a genetic algorithm for multi-model assembly lines considering worker change in allocation

Jiahua Weng, Hisashi Onari

    Research output: Contribution to journalArticle

    Abstract

    This paper focuses on multi-model assembly line production, where each model is produced in small lots, and operations differ obviously among models (e.g., number of operations, operation precedence constraints and so forth). At the same time, according to workers' different experiences and capabilities, their work skills differ largely among operations, and the processing time of a given operation is diverse among workers. Taking total processing time (makespan) as objective function, the line operation planning problem of such an assembly line is discussed, which includes three sub-problems: (i) assigning operations of each lot to workstations, (ii) allocating workers to workstations for each lot, and (iii) determining the lot production sequence for the line. In order to reduce the cycle time (CT) of each lot considering the obvious difference in worker skills, the worker allocation schemes of each lot may be different. Therefore, the switch time (SWT) caused by different worker allocation between adjacent lots has to be dealt with as well. Since this is a complicated and large-scale problem, an algorithm based on genetic algorithm (GA) is developed in this paper. A heuristic crossover procedure is proposed, which focuses on not only the workload balance loss of each lot but also the switch loss between adjacent lots. Our approach is tested and confirmed to be effective for shortening makespan compared to the following two production approaches: SPPT-oriented production approach and Cr-oriented production approach.

    Original languageEnglish
    Pages (from-to)304-311
    Number of pages8
    JournalJournal of Japan Industrial Management Association
    Volume59
    Issue number4
    Publication statusPublished - 2008

    Fingerprint

    Assembly Line
    Multi-model
    Genetic algorithms
    Planning
    Genetic Algorithm
    Time switches
    Switch
    Adjacent
    Processing
    Precedence Constraints
    Line
    Large-scale Problems
    Switches
    Assembly line
    Operations planning
    Genetic algorithm
    Workers
    Workload
    Crossover
    Objective function

    Keywords

    • Genetic algorithm
    • Lot sequencing
    • Multi-model line balancing
    • Operation assignment
    • Worker allocation

    ASJC Scopus subject areas

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

    Cite this

    Operation planning based on a genetic algorithm for multi-model assembly lines considering worker change in allocation. / Weng, Jiahua; Onari, Hisashi.

    In: Journal of Japan Industrial Management Association, Vol. 59, No. 4, 2008, p. 304-311.

    Research output: Contribution to journalArticle

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