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A comparison of the performance of artificial intelligence techniques for optimizing the number of kanbans

Author

Listed:
  • C Alabas

    (Gazi University, Maltepe)

  • F Altiparmak

    (Gazi University, Maltepe)

  • B Dengiz

    (Gazi University, Maltepe)

Abstract

This paper discusses the use of modern heuristic techniques coupled with a simulation model of a Just in Time system to find the optimum number of kanbans while minimizing cost. Three simulation search heuristic procedures based on Genetic Algorithms, Simulated Annealing, and Tabu Search are developed and compared both with respect to the best results achieved by each algorithm in a limited time span and their speed of convergence to the results. In addition, a Neural Network metamodel is developed and compared with the heuristic procedures according to the best results. The results indicate that Tabu Search performs better than the other heuristics and Neural Network metamodel in terms of computational effort.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:8:d:10.1057_palgrave.jors.2601395
    DOI: 10.1057/palgrave.jors.2601395
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    Citations

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    Cited by:

    1. Yamamoto, Hidehiko & Abu Qudeiri, Jaber & Marui, Etsuo, 2008. "Definition of FTL with bypass lines and its simulator for buffer size decision," International Journal of Production Economics, Elsevier, vol. 112(1), pages 18-25, March.
    2. Ohno, Katsuhisa, 2011. "The optimal control of just-in-time-based production and distribution systems and performance comparisons with optimized pull systems," European Journal of Operational Research, Elsevier, vol. 213(1), pages 124-133, August.
    3. 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.
    4. Asefeh Hasani Goodarzi & Seyed Hessameddin Zegordi, 2020. "Vehicle routing problem in a kanban controlled supply chain system considering cross-docking strategy," Operational Research, Springer, vol. 20(4), pages 2397-2425, December.

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