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Bilevel mixed-integer nonlinear programming for integrated scheduling in a supply chain network

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Abstract

An integrated scheduling problem under a make-to-order supply chain network is addressed. This problem considers integrated production and transportation scheduling with realistic supply chain features such as unrelated parallel shop and product batch-based transportation. The mathematical model for this problem is presented, which is formulated as a bilevel mixed-integer nonlinear program. A novel bilevel evolutionary optimization model based on memetic algorithm is proposed to resolve this problem because the problem is hard-to-tackle for mathematical programming techniques and traditional intelligent techniques. The effectiveness of the proposed optimization model is validated through a series of numerical experiments. The experimental results also confirmed that the proposed optimization model is superior to other three intelligent optimization models.

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Acknowledgements

This paper is supported partly by the National Natural Science Foundation of China under Grant Nos. 71532007, 71131006 and 71172197.

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Authors and Affiliations

  1. Business School, Sichuan University, Chengdu, China

    Jianchao Yang & Li Luo

  2. College of Computer Science, Sichuan University, Chengdu, China

    Feng Guo & Xiaoming Ye

  3. School of Cybersecurity, Chengdu University of Information Technology, Chengdu, China

    Xiaoming Ye

Authors
  1. Jianchao Yang
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  2. Feng Guo
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  3. Li Luo
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  4. Xiaoming Ye
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Correspondence to Xiaoming Ye.

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Appendix

Appendix

See Tables 7, 8, and 9 in Appendix.

Table 7 Information of order groups in experiment 1
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Table 8 Information of order groups in experiment 2
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Table 9 Information of order groups in experiment 3
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Yang, J., Guo, F., Luo, L. et al. Bilevel mixed-integer nonlinear programming for integrated scheduling in a supply chain network. Cluster Comput 22 (Suppl 6), 15517–15532 (2019). https://doi.org/10.1007/s10586-018-2673-2

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  • DOI: https://doi.org/10.1007/s10586-018-2673-2

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