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Optimization of manufacturing systems using a neural network metamodel with a new training approach

Author

Listed:
  • B Dengiz

    (Baskent University)

  • C Alabas-Uslu

    (Maltepe University)

  • O Dengiz

    (D&D Consulting)

Abstract

In this study, two manufacturing systems, a kanban-controlled system and a multi-stage, multi-server production line in a diamond tool production system, are optimized utilizing neural network metamodels (tst_NNM) trained via tabu search (TS) which was developed previously by the authors. The most widely used training algorithm for neural networks has been back propagation which is based on a gradient technique that requires significant computational effort. To deal with the major shortcomings of back propagation (BP) such as the tendency to converge to a local optimal and a slow convergence rate, the TS metaheuristic method is used for the training of artificial neural networks to improve the performance of the metamodelling approach. The metamodels are analysed based on their ability to predict simulation results versus traditional neural network metamodels that have been trained by BP algorithm (bp_NNM). Computational results show that tst_NNM is superior to bp_NNM for both of the manufacturing systems.

Suggested Citation

  • B Dengiz & C Alabas-Uslu & O Dengiz, 2009. "Optimization of manufacturing systems using a neural network metamodel with a new training approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1191-1197, September.
  • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:9:d:10.1057_palgrave.jors.2602620
    DOI: 10.1057/palgrave.jors.2602620
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    References listed on IDEAS

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    1. R D Hurrion & S Birgil, 1999. "A comparison of factorial and random experimental design methods for the development of regression and neural network simulation metamodels," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(10), pages 1018-1033, October.
    2. C Alabas & F Altiparmak & B Dengiz, 2002. "A comparison of the performance of artificial intelligence techniques for optimizing the number of kanbans," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(8), pages 907-914, August.
    3. Mansooreh Mollaghasemi & Kenneth LeCroy & Michael Georgiopoulos, 1998. "Application of Neural Networks and Simulation Modeling in Manufacturing System Design," Interfaces, INFORMS, vol. 28(5), pages 100-114, October.
    4. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
    5. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    6. Chambers, M. & Mount-Campbell, C. A., 2002. "Process optimization via neural network metamodeling," International Journal of Production Economics, Elsevier, vol. 79(2), pages 93-100, September.
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