A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability

Jiahua Weng, Xianchao Wu, Hisashi Onari

    研究成果: Conference contribution

    抄録

    This paper focuses on line process planning problem of multi-model (product type) assembly lines. The planning 1) assigns workers/operations to workstations for each model and 2) decides the production sequence of models. Since it is an NP-complete problem, a Genetic Algorithm (GA) based approach is adopted. Given the number of available workstations, a hybrid GA framework is proposed to find the Pareto optimization set instead of only one trade-off solution. Two parent selection strategies, by making use of Niched Pareto and weighted objective functions, are applied and compared. Moreover, a local heuristic strategy on worker allocation and operations assignment is proposed to avoid local optimal solutions and for obtaining better Pareto solution sets. Numerical analysis are conducted and the selection strategies using weighted objective functions is verified to perform better. Finally, the proposed heuristic strategy is confirmed to bring a further improvement of optimizing all the objectives.

    元の言語English
    ホスト出版物のタイトル21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings
    出版者Fraunhofer-Verlag
    ISBN(印刷物)9783839602935
    出版物ステータスPublished - 2011
    イベント21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Stuttgart
    継続期間: 2011 7 312011 8 4

    Other

    Other21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011
    Stuttgart
    期間11/7/3111/8/4

    Fingerprint

    Process planning
    Genetic algorithms
    Numerical analysis
    Computational complexity
    Planning

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Computer Science Applications
    • Industrial and Manufacturing Engineering

    これを引用

    Weng, J., Wu, X., & Onari, H. (2011). A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability. : 21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings Fraunhofer-Verlag.

    A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability. / Weng, Jiahua; Wu, Xianchao; Onari, Hisashi.

    21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings. Fraunhofer-Verlag, 2011.

    研究成果: Conference contribution

    Weng, J, Wu, X & Onari, H 2011, A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability. : 21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings. Fraunhofer-Verlag, 21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011, Stuttgart, 11/7/31.
    Weng J, Wu X, Onari H. A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability. : 21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings. Fraunhofer-Verlag. 2011
    Weng, Jiahua ; Wu, Xianchao ; Onari, Hisashi. / A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability. 21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings. Fraunhofer-Verlag, 2011.
    @inproceedings{9178baf7e0034d9a89f42179f80ce0eb,
    title = "A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability",
    abstract = "This paper focuses on line process planning problem of multi-model (product type) assembly lines. The planning 1) assigns workers/operations to workstations for each model and 2) decides the production sequence of models. Since it is an NP-complete problem, a Genetic Algorithm (GA) based approach is adopted. Given the number of available workstations, a hybrid GA framework is proposed to find the Pareto optimization set instead of only one trade-off solution. Two parent selection strategies, by making use of Niched Pareto and weighted objective functions, are applied and compared. Moreover, a local heuristic strategy on worker allocation and operations assignment is proposed to avoid local optimal solutions and for obtaining better Pareto solution sets. Numerical analysis are conducted and the selection strategies using weighted objective functions is verified to perform better. Finally, the proposed heuristic strategy is confirmed to bring a further improvement of optimizing all the objectives.",
    keywords = "Assembly line balancing, Genetic algorithm, Multi-model, Multi-objective, Worker ability",
    author = "Jiahua Weng and Xianchao Wu and Hisashi Onari",
    year = "2011",
    language = "English",
    isbn = "9783839602935",
    booktitle = "21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings",
    publisher = "Fraunhofer-Verlag",

    }

    TY - GEN

    T1 - A multi-objective approach based on genetic algorithm for multi-model line process planning considering difference in worker ability

    AU - Weng, Jiahua

    AU - Wu, Xianchao

    AU - Onari, Hisashi

    PY - 2011

    Y1 - 2011

    N2 - This paper focuses on line process planning problem of multi-model (product type) assembly lines. The planning 1) assigns workers/operations to workstations for each model and 2) decides the production sequence of models. Since it is an NP-complete problem, a Genetic Algorithm (GA) based approach is adopted. Given the number of available workstations, a hybrid GA framework is proposed to find the Pareto optimization set instead of only one trade-off solution. Two parent selection strategies, by making use of Niched Pareto and weighted objective functions, are applied and compared. Moreover, a local heuristic strategy on worker allocation and operations assignment is proposed to avoid local optimal solutions and for obtaining better Pareto solution sets. Numerical analysis are conducted and the selection strategies using weighted objective functions is verified to perform better. Finally, the proposed heuristic strategy is confirmed to bring a further improvement of optimizing all the objectives.

    AB - This paper focuses on line process planning problem of multi-model (product type) assembly lines. The planning 1) assigns workers/operations to workstations for each model and 2) decides the production sequence of models. Since it is an NP-complete problem, a Genetic Algorithm (GA) based approach is adopted. Given the number of available workstations, a hybrid GA framework is proposed to find the Pareto optimization set instead of only one trade-off solution. Two parent selection strategies, by making use of Niched Pareto and weighted objective functions, are applied and compared. Moreover, a local heuristic strategy on worker allocation and operations assignment is proposed to avoid local optimal solutions and for obtaining better Pareto solution sets. Numerical analysis are conducted and the selection strategies using weighted objective functions is verified to perform better. Finally, the proposed heuristic strategy is confirmed to bring a further improvement of optimizing all the objectives.

    KW - Assembly line balancing

    KW - Genetic algorithm

    KW - Multi-model

    KW - Multi-objective

    KW - Worker ability

    UR - http://www.scopus.com/inward/record.url?scp=84923433754&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84923433754&partnerID=8YFLogxK

    M3 - Conference contribution

    AN - SCOPUS:84923433754

    SN - 9783839602935

    BT - 21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings

    PB - Fraunhofer-Verlag

    ER -