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Task allocation optimization in collaborative customized product development based on double-population adaptive genetic algorithm

Author

Listed:
  • Beifang Bao

    (Chongqing University
    Chongqing University)

  • Yu Yang

    (Chongqing University
    Chongqing University)

  • Qian Chen

    (Chongqing University
    Chongqing University)

  • Aijun Liu

    (Xidian University
    Chongqing University)

  • Jiali Zhao

    (Chongqing University
    Chongqing University)

Abstract

Task allocation is one of the most important activities in the process of collaborative customized product development. At present, how to allocate the collaborative development tasks scientifically and rationally becomes one of the hot research issues in the field of product development. Although many scholars in academia has made a significant contribution to the problem of task allocation and achieved many useful results, the research work of collaborative development task allocation for product customization is still lacking. Therefore, in view of the insufficient consideration on task fitness and task coordination for task allocation in collaborative customized product development at present, research work in this paper is conducted based on the analysis of collaborative customized product development process and task allocation strategy. The definition and calculation formula of task fitness and task coordination efficiency are given firstly, then the multi-objective optimization model of product customization task allocation is constructed and the solving method based on the model of double-population adaptive genetic algorithm is proposed. Finally, the feasibility and the effectiveness of task allocation algorithm are tested and verified by the example of a 5MW wind turbine product development project.

Suggested Citation

  • Beifang Bao & Yu Yang & Qian Chen & Aijun Liu & Jiali Zhao, 2016. "Task allocation optimization in collaborative customized product development based on double-population adaptive genetic algorithm," Journal of Intelligent Manufacturing, Springer, vol. 27(5), pages 1097-1110, October.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:5:d:10.1007_s10845-014-0937-0
    DOI: 10.1007/s10845-014-0937-0
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    References listed on IDEAS

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    1. Robert P. Smith & Steven D. Eppinger, 1997. "A Predictive Model of Sequential Iteration in Engineering Design," Management Science, INFORMS, vol. 43(8), pages 1104-1120, August.
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