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Balancing stochastic U-lines using particle swarm optimization

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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.

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Authors and Affiliations

  1. Department of Industrial Engineering, Erciyes University, Kayseri, Turkey

    Emel Kızılkaya Aydoğan

  2. Department of Management and Organization, Develi Vocational College, Erciyes University, Develi, Kayseri, Turkey

    Yılmaz Delice

  3. Department of Industrial Engineering, Gazi University, Ankara, Turkey

    Uğur Özcan & Cevriye Gencer

  4. Defense Sciences Institute, Turkish Military Academy, Ankara, Turkey

    Özkan Bali

Authors
  1. Emel Kızılkaya Aydoğan
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  2. Yılmaz Delice
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  3. Uğur Özcan
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  4. Cevriye Gencer
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  5. Özkan Bali
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Correspondence to Uğur Özcan.

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Aydoğan, E.K., Delice, Y., Özcan, U. et al. Balancing stochastic U-lines using particle swarm optimization. J Intell Manuf 30, 97–111 (2019). https://doi.org/10.1007/s10845-016-1234-x

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  • DOI: https://doi.org/10.1007/s10845-016-1234-x

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