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The Research of Using Ant Colony Algorithm in Solving Sequencing Problem of Mixed Model Assembly Lines with Multi-objectives

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5227))

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Abstract

Mixed model assembly lines (MMAL) sequencing problem is a typical NP-hard problem. It’s important to search for an optimal sequence to maximize the efficiency of production lines. Therefore this work proposes a new mathematic programming model for measuring the efficiency of MMAL. A modified ant colony algorithm (MACA) is developed to determine a sequence which optimizes the objective function with elitist strategy. The experimental results indicate the applicability of the proposed objective function and availability of the algorithm in solving this problem.

This paper is supported by the National Natural Science Foundation of China, No. 50575137 and the National High-Tech Research and Development Plan of China(863 Program), No.2007AA04Z109.

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References

  1. Dar-El, E.M., Cucuy, S.: Optimal Mixed-model Sequencing for Balanced Assembly Lines. Omega 5, 333–342 (1977)

    Article  Google Scholar 

  2. Xiaobo, Z., Zhou, Z., Asres, A.: A Note on Toyota’s Goal of Sequencing Mixed Models on an Assembly Line. Computers & Industrial Engineering 36, 57–65 (1999)

    Article  Google Scholar 

  3. Becker, C., Scholl, A.: A Survey on Problems and Methods in Generalized Assembly Line Balancing. European Journal of Operational Research 168, 694–715 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  4. Dar-El, E.M.: Mixed-model Assembly Line Sequencing Problems. Omega 6, 313–323 (1978)

    Article  Google Scholar 

  5. Kubiak, W.: Minimizing Variation of Production Rates in Just-in-time Systems: A Survey. European Journal of Operational Research 66, 259–271 (1993)

    Article  MATH  Google Scholar 

  6. Karabati, S., Sayin, S.: Assembly Line Balancing in a Mixed-model Sequencing Environment with Synchronous transfers. European Journal of OR 149, 417–429 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  7. Dorigo, M., Gambardella, L.M.: Ant Colonies for the Travelling Salesman Problem. Biosystems 43, 73–81 (1997)

    Article  Google Scholar 

  8. Shyu, S.J., Lin, B.M.T., Hsiao, T.S.: Ant Colony Optimization for the Cell Assignment Problem in PCS Networks. Computers & Operations Research 33, 1713–1740 (2006)

    Article  MATH  Google Scholar 

  9. Gagne, C., Gravel, M., Price, W.L.: Solving Real Car Sequencing Problems with Ant Colony Optimization. European Journal of Operational Research 174, 1427–1448 (2006)

    Article  MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Computer Integrated Manufacturing Research Institute, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Qiong Zhu, Lihui Wu & Jie Zhang

Authors
  1. Qiong Zhu
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  2. Lihui Wu
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  3. Jie Zhang
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Editor information

De-Shuang Huang Donald C. Wunsch II Daniel S. Levine Kang-Hyun Jo

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© 2008 Springer-Verlag Berlin Heidelberg

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Zhu, Q., Wu, L., Zhang, J. (2008). The Research of Using Ant Colony Algorithm in Solving Sequencing Problem of Mixed Model Assembly Lines with Multi-objectives. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_71

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  • DOI: https://doi.org/10.1007/978-3-540-85984-0_71

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85983-3

  • Online ISBN: 978-3-540-85984-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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