Journal of Intelligent Manufacturing

, Volume 27, Issue 5, pp 1097–1110 | Cite as

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

  • Beifang Bao
  • Yu Yang
  • Qian Chen
  • Aijun Liu
  • Jiali Zhao
Article
First Online:
Received:
Accepted:

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.

Keywords

Collaborative customized product development Task allocation Task fitness Task coordination efficiency Double-population adaptive genetic algorithm 
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Notes

Acknowledgments

This research is funded by the National Nature Science Foundation of China (No. 71071173), joint supported by Research Fund for the Doctoral Program of Higher Education of China (20090191110004),MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No. 13XJC630011), Ministry of Education research fund for the Doctoral program of higher education (No. 20120184120040), Central University Science Research Foundation of China (No. K5051306006) and the teacher innovation project of Xidian University (No. K5051306013).

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Beifang Bao
    • 1
    • 3
  • Yu Yang
    • 1
    • 3
  • Qian Chen
    • 1
    • 3
  • Aijun Liu
    • 2
    • 3
  • Jiali Zhao
    • 1
    • 3
  1. 1.State Key Laboratory of Mechanical TransmissionChongqing UniversityChongqingChina
  2. 2.Economy and Management SchoolXidian UniversityXi’anChina
  3. 3.Department of Industrial Engineering, College of Mechanical EngineeringChongqing UniversityChongqingChina

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