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An enhanced branch-and-price algorithm for the integrated production and transportation scheduling problem

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  • Peiyang He
  • Kunpeng Li
  • P. N. Ram Kumar

Abstract

Industry 4.0 technologies, such as artificial intelligence, the internet of things and 3D printing are aiding the manufacturers by complementing their skilled workforce and transforming the way factories are run. This paper studies an integrated production and transportation scheduling problem in the context of the spare parts supply chain by integrating 3D printing with JIT delivery systems. This work aims to find a synchronised production and distribution schedule that minimises the weighted sum of delivery times and transportation costs. Based on the characteristics of the problem, we propose a new set-covering formulation. An enhanced branch-and-price algorithm is designed to solve the problem instances to optimality. To expedite the column generation process, two acceleration strategies are also used. The computational results are in favour of the proposed algorithm and the acceleration strategies. Further, the results indicate that integrating the production and transportation scheduling decisions leads to an average savings of about 16.27% of the total costs.

Suggested Citation

  • Peiyang He & Kunpeng Li & P. N. Ram Kumar, 2022. "An enhanced branch-and-price algorithm for the integrated production and transportation scheduling problem," International Journal of Production Research, Taylor & Francis Journals, vol. 60(6), pages 1874-1889, March.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:6:p:1874-1889
    DOI: 10.1080/00207543.2021.1876941
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    Cited by:

    1. Berghman, Lotte & Kergosien, Yannick & Billaut, Jean-Charles, 2023. "A review on integrated scheduling and outbound vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 1-23.
    2. Jose M. Framinan & Paz Perez-Gonzalez & Victor Fernandez-Viagas, 2023. "An overview on the use of operations research in additive manufacturing," Annals of Operations Research, Springer, vol. 322(1), pages 5-40, March.

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