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Modelling and numerical analysis of seru loading problem under uncertainty

Author

Listed:
  • Lan Luo
  • Zhe Zhang
  • Yong Yin

Abstract

As a flexible manufacturing system, seru seisan has been proven to be more competitive in a volatile market than traditional assembly line. In this system, seru loading plays an essential role to deal with the fluctuating demands and uncertain product types. Unfortunately, in practice, seru loading decision-making is mainly based on the supervisor's experience instead of the theoretical research. In this situation, seru loading in a single period under uncertainty is considered in this paper, meanwhile, a fuzzy random bi-objective model is developed to minimise the makespan and the total tardiness penalty cost. To deal with the fuzzy random variables, these uncertain parameters are transformed into the trapezoidal fuzzy variables, which are subsequently de-fuzzified by the optimistic-pessimistic adjustment index Me. After obtaining the equivalent crisp model, a heuristic algorithm based on enumerating feasible solutions is designed. Finally, to demonstrate the practicability, a numerical example is applied, and the generated results verify the efficiency of the proposed model and algorithm for seru loading problem. [Received: 28 April 2016; Revised: 28 July 2016; Accepted: 13 September 2016]

Suggested Citation

  • Lan Luo & Zhe Zhang & Yong Yin, 2017. "Modelling and numerical analysis of seru loading problem under uncertainty," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 11(2), pages 185-204.
    • Handle: RePEc:ids:eujine:v:11:y:2017:i:2:p:185-204
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    Cited by:

    1. Zhang, Zhe & Gong, Xue & Song, Xiaoling & Yin, Yong & Lev, Benjamin & Chen, Jie, 2022. "A column generation-based exact solution method for seru scheduling problems," Omega, Elsevier, vol. 108(C).
    2. Zhang, Zhe & Song, Xiaoling & Huang, Huijung & Zhou, Xiaoyang & Yin, Yong, 2022. "Logic-based Benders decomposition method for the seru scheduling problem with sequence-dependent setup time and DeJong’s learning effect," European Journal of Operational Research, Elsevier, vol. 297(3), pages 866-877.
    3. Zhe Zhang & Xiaoling Song & Huijun Huang & Yong Yin & Benjamin Lev, 2022. "Scheduling problem in seru production system considering DeJong’s learning effect and job splitting," Annals of Operations Research, Springer, vol. 312(2), pages 1119-1141, May.

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