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Design and control of manufacturing systems: a discrete event optimisation methodology

Author

Listed:
  • Giulia Pedrielli
  • Andrea Matta
  • Arianna Alfieri
  • Mengyi Zhang

Abstract

Simulation optimisation has gained a great attention due to its success in the design of complex manufacturing systems. In this paper, we look at manufacturing as a special class of queueing systems and propose the Discrete Event Optimisation (DEO) methodology, which provides a formal way to develop integrated mathematical models for the simultaneous simulation and optimisation. In the case, the obtained model is a mixed integer linear programming model; the methodology provides a formal way to generate approximations of them. The analytical properties of DEO models are analysed for the first time in the framework of sample path optimisation and mathematical programming. The methodology represents a reference for the use of mathematical programming as a way to model simulation optimisation for queueing systems. The applicability of the DEO methodology to complex problems is showed using the task and buffer allocation problem in a production line.

Suggested Citation

  • Giulia Pedrielli & Andrea Matta & Arianna Alfieri & Mengyi Zhang, 2018. "Design and control of manufacturing systems: a discrete event optimisation methodology," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 543-564, January.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:543-564
    DOI: 10.1080/00207543.2017.1412532
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    Cited by:

    1. Wenjie Wang & Guangdong Tian & Gang Yuan & Duc Truong Pham, 2023. "Energy-time tradeoffs for remanufacturing system scheduling using an invasive weed optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1065-1083, March.
    2. Mehmet Ulaş Koyuncuoğlu & Leyla Demir, 2021. "A comparison of combat genetic and big bang–big crunch algorithms for solving the buffer allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1529-1546, August.
    3. Yagmur S. Gök & Silvia Padrón & Maurizio Tomasella & Daniel Guimarans & Cemalettin Ozturk, 2023. "Constraint-based robust planning and scheduling of airport apron operations through simheuristics," Annals of Operations Research, Springer, vol. 320(2), pages 795-830, January.

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