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Intelligent multi-objective decision-making model with RFID technology for production planning

Author

Listed:
  • Wong, W.K.
  • Guo, Z.X.
  • Leung, S.Y.S

Abstract

A multi-objective production planning problem in the labor-intensive manufacturing industry is investigated. An intelligent and real-time multi-objective decision-making model is developed to provide timely and effective solutions for this problem by integrating RFID technology with intelligent optimization techniques, in which RFID technology is used to collect real-time production data, a novel (μ/ρ+λ)-evolution strategy process with self-adaptive population size and novel recombination operation is proposed and integrated with effective non-dominated sorting and pruning techniques to generate Pareto optimal solutions for real-world production. Experiments based on industrial data were conducted to evaluate the effectiveness of the proposed model. Experimental results show that the proposed model can effectively solve the investigated problem by providing production planning solutions superior to industrial solutions.

Suggested Citation

  • Wong, W.K. & Guo, Z.X. & Leung, S.Y.S, 2014. "Intelligent multi-objective decision-making model with RFID technology for production planning," International Journal of Production Economics, Elsevier, vol. 147(PC), pages 647-658.
    • Handle: RePEc:eee:proeco:v:147:y:2014:i:pc:p:647-658
    DOI: 10.1016/j.ijpe.2013.05.011
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    References listed on IDEAS

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    1. Sahin, Funda & Powell Robinson, E. & Gao, Li-Lian, 2008. "Master production scheduling policy and rolling schedules in a two-stage make-to-order supply chain," International Journal of Production Economics, Elsevier, vol. 115(2), pages 528-541, October.
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    Cited by:

    1. Guo, Z.X. & Ngai, E.W.T. & Yang, Can & Liang, Xuedong, 2015. "An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment," International Journal of Production Economics, Elsevier, vol. 159(C), pages 16-28.
    2. Yingfeng Zhang & Geng Zhang & Yang Liu & Di Hu, 2017. "Research on services encapsulation and virtualization access model of machine for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1109-1123, June.
    3. Dai, Hongyan & Ge, Ling & Zhou, Weihua, 2015. "A design method for supply chain traceability systems with aligned interests," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 14-24.
    4. Gong, Qiguo & Yang, Yuru & Wang, Shouyang, 2014. "Information and decision-making delays in MRP, KANBAN, and CONWIP," International Journal of Production Economics, Elsevier, vol. 156(C), pages 208-213.
    5. Wei Wang & Jingjie Chen & Qi Liu & Zhaoxia Guo, 2018. "Green Project Planning with Realistic Multi-Objective Consideration in Developing Sustainable Port," Sustainability, MDPI, vol. 10(7), pages 1-15, July.

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