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Balancing stochastic U-lines using particle swarm optimization

Author

Listed:
  • Emel Kızılkaya Aydoğan

    (Erciyes University)

  • Yılmaz Delice

    (Develi Vocational College, Erciyes University)

  • Uğur Özcan

    (Gazi University)

  • Cevriye Gencer

    (Gazi University)

  • Özkan Bali

    (Turkish Military Academy)

Abstract

U-lines are important parts of the Just-In-Time production system in order to improve productivity and quality. In real life applications of assembly lines, the tasks may have varying execution times defined as a probability distribution. In this study, a novel particle swarm optimization algorithm is proposed to solve the U-line balancing problem with stochastic task times. A computational study is conducted to compare the performance of the proposed approach to the existing methods in the literature. The results of the computational study show that the proposed approach performs quite effectively. It also yields good solutions for all test problems within a short computational time.

Suggested Citation

  • Emel Kızılkaya Aydoğan & Yılmaz Delice & Uğur Özcan & Cevriye Gencer & Özkan Bali, 2019. "Balancing stochastic U-lines using particle swarm optimization," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 97-111, January.
    • Handle: RePEc:spr:joinma:v:30:y:2019:i:1:d:10.1007_s10845-016-1234-x
    DOI: 10.1007/s10845-016-1234-x
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    References listed on IDEAS

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    Cited by:

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    3. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    4. Daniele Marini & Jonathan R. Corney, 2021. "Concurrent optimization of process parameters and product design variables for near net shape manufacturing processes," Journal of Intelligent Manufacturing, Springer, vol. 32(2), pages 611-631, February.

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