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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.

Author information

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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Corresponding author

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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