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Research on flexible job shop scheduling with low-carbon technology based on quantum bacterial foraging optimization

Author

Listed:
  • Tao Ning
  • Zi Wang
  • Xiaodong Duan
  • Xiangdong Liu

Abstract

In order to further reduce the carbon emission of manufacturing process in flexible job shop, a multi-objective integrated optimization model of flexible job-shop scheduling (FJSP) is proposed. A mathematics model is built in this paper to minimize makespan, total workload of machines and carbon emissions of machines and to optimize process method of each machine characteristic, process sequence and machine allocation. Considering many parameters are interactional and to be optimized in the proposed model, a quantum bacterial foraging optimization is designed to code the related parameters. On the basis of Kacem example through experimental simulation, the performance of the proposed method in the paper was analysed with ANOVA, and by comparing with the algorithms of current separated optimization method of process planning and scheduling, the effect of proposed integrated optimization model on reducing carbon emission in practical requirements of FJSP is verified.

Suggested Citation

  • Tao Ning & Zi Wang & Xiaodong Duan & Xiangdong Liu, 2021. "Research on flexible job shop scheduling with low-carbon technology based on quantum bacterial foraging optimization," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 16(3), pages 761-769.
    • Handle: RePEc:oup:ijlctc:v:16:y:2021:i:3:p:761-769.
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    File URL: http://hdl.handle.net/10.1093/ijlct/ctab005
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