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A Two-Level Genetic Algorithm for Scheduling in Assembly Islands with Fixed-Position Layouts

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Global Perspective for Competitive Enterprise, Economy and Ecology

Part of the book series: Advanced Concurrent Engineering ((ACENG))

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Abstract

This paper focuses on the scheduling problem in assembly islands environment with fixed layouts. A fixed-position assembly line is always used when products (e.g., ships and planes) are too fragile, large or heavy to move. In such configuration, products normally remain in one location for its entire manufacturing period while machines, materials and workers are moved to an assembly site called an assembly island. Such layouts can afford necessary flexibility and competitive operational efficiency for products of modest variety and production volumes. However, the high dynamics of material, equipment and manpower flows in assembly islands make the production scheduling quite difficult. The authors give the definition and mathematical model for the scheduling problem. A two-level genetic algorithm is used to obtain a near optimal solution to minimize the makespan. Experimental results show that this algorithm is more effective in airline or ship industrial manufactures than in other machine or tool final assembly companies. It also can be found that some function of the number of jobs and the number of islands is the most important factor to the time of scheduling.

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7 References

  1. E. Trostmann, F. Conrad, H. Holm and O. Madsen, “Cybernetic modeling and control in integrated production systems – A project review”, Proceedings of the Eighth IPS Research Seminar, Denmark, pp. 213-225, 22-24 March 1993.

    Google Scholar 

  2. G. Q. Huang, Y. F. Zhang, and P. Y. Jiang, “RFID-based wireless manufacturing for walking-worker assembly islands with fixed-position layouts”, in Robotics and Computer-Integrated Manufacturing, vol. 23, pp. 469-477, 2007.

    Article  Google Scholar 

  3. Q. Wang, G W Owen, and A R Mileham, “Comparison between fixed-and walkingworker assembly lines”, in Proc IMechE Part B: J.Engineering Manufacturing, vol. 219, pp. 845–848, 2005.

    Article  Google Scholar 

  4. P. E. Chin, G. Q. Huang and Xin Chen, “Scheduling for Assembly Islands with Fixed- Position Layouts”, DET 2008, Nantes, France.

    Google Scholar 

  5. T.C.Cheng, J.N.D.Gupta and G.Q.Wang, “A review of flowshop scheduling research with setup times” in Operations Management, vol. 9, no. 3, pp. 262–282, 2000.

    Google Scholar 

  6. Y. H. Lee and M. Pinedo, “Scheduling jobs on parallel machines with sequencedependent setup times”, in European Journal of Operational Research, Vol. 100, pp. 464-474, 1997.

    Article  MATH  Google Scholar 

  7. P. B. Luh, L. Gou and Y. Zhang, “Job shop scheduling with group-dependent setups, finite buffers, and long time horizon”, in Annals of Operations Research, 76, pp.233- 259, 1998.

    Article  MATH  Google Scholar 

  8. I. Rechberg, “Opimierung technicher Systeme nach Prinzipien der biologischen Evolution”, Problemate, Frommann-Holzboog, 1973.

    Google Scholar 

  9. J. H. Holland, “Adaptation in Natural and Artificial Systems”, The University of Michigan Press, Ann Arbor, 1975.

    Google Scholar 

  10. H. P. Schwefel, “Numerische Optimierung von Computer-Modellen mittels del Evolutionsstrategie”,Birkhauser, Basel, 1977.

    Google Scholar 

  11. D. E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine Learning”, Addison-Wesley, Reading, Mass., 1989.

    MATH  Google Scholar 

  12. Z. Michalewicz, “Genetic Algorithms + Data Structures = Evolution Programs”, Springer, Berlin, 1997.

    Google Scholar 

  13. N. B. Ho, J. C. Tay and E. M. K. Lai, “An effective architecture for learning and evolving flexible job-shop schedules”, European Journal of Operational Research, 179, pp. 316-333, 2007.

    Article  MATH  Google Scholar 

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Correspondence to Wei Qin .

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© 2009 Springer London

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Qin, W., Huang, G. (2009). A Two-Level Genetic Algorithm for Scheduling in Assembly Islands with Fixed-Position Layouts. In: Chou, SY., Trappey, A., Pokojski, J., Smith, S. (eds) Global Perspective for Competitive Enterprise, Economy and Ecology. Advanced Concurrent Engineering. Springer, London. https://doi.org/10.1007/978-1-84882-762-2_2

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  • DOI: https://doi.org/10.1007/978-1-84882-762-2_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-761-5

  • Online ISBN: 978-1-84882-762-2

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