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Analysis of Mix-Model Assembly Line Balancing with Enhanced Genetic Algorithm

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Recent Advances in Computer Science and Information Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 126))

Abstract

To seek the optimal analysis of line balancing in mix-model assembly line, Author comes up with one new enhanced Genetic Algorithm which takes some new engineering constraints into consideration as well as introducing SA factor to avoid premature. Through applying analysis on one real use case, it proves good result of optimization efficiency and quality.

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References

  1. Cao, Z., Zhu, Y., Zhao, M., et al.: Optimal research on balancing and sequencing of mixed model assembly lines. Information and Control 33(6), 660–664 (2004) (in Chinese)

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  2. Yu, Z., Su, P.: Combining genetic algorithm and simulation analysis for mix-model assembly line balancing problem. Computer Integrated Manufacturing Systems 14(6) (June 2008) (in Chinese)

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  3. Ling, W.: Research on balancing of mix-model assembly line workstations based on genetic algorithm. Journal of Hefei University of Technology 31(8) (August 2008) (in Chinese)

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  4. Cai, M., Wang, F., Yang, S.: Material supply on car assembly line with JIT manufacturing style. Manufacturing Automation 28 (December 2006) (in Chinese)

    Google Scholar 

  5. Modeling of ALB Problem and its optimization. Journal System Simulation 5(11) (October 1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Mechnical College, University of Science and Technology Beijing, No.30 Xueyuan Road, Haidian district, Beijing, China

    Xianfeng Li & Shaohua Dong

Authors
  1. Xianfeng Li
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  2. Shaohua Dong
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Editor information

Editors and Affiliations

  1. , College of Communication Engineering, Jilin University, Room 313, Building No.1, Changchun, Nanhu Avenue 5372, Jilin, 130012, China, People's Republic

    Zhihong Qian

  2. , Department of Electrical Engineering, The University of Mississippi, Anderson Hall 314, Mississippi, 38677, Mississippi, USA

    Lei Cao

  3. , Department of Electrical and Computer En, Naval Postgraduate School, Rm. 452 Spanagel Bldg. 232, Dyer Road 833, Monterey, 93943-5121, California, USA

    Weilian Su

  4. , Faculty of Computing, London Metropolitan University, Holloway Road 166-220, London, N7 8DB, United Kingdom

    Tingkai Wang

  5. , College of Software, Changchun University of Science and Tech, Changchun, Jilin, 130022, China, People's Republic

    Huamin Yang

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Li, X., Dong, S. (2012). Analysis of Mix-Model Assembly Line Balancing with Enhanced Genetic Algorithm. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25766-7_13

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  • DOI: https://doi.org/10.1007/978-3-642-25766-7_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25765-0

  • Online ISBN: 978-3-642-25766-7

  • eBook Packages: EngineeringEngineering (R0)

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