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An efficient buffer design algorithm for production line profit maximization

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  • Shi, Chuan
  • Gershwin, Stanley B.

Abstract

In this paper, we present an effective algorithm for maximizing profits through buffer size optimization for production lines. We consider both buffer space cost and average inventory cost with distinct cost coefficients for different buffers, and we include a nonlinear production rate constraint. To solve the problem, a corresponding unconstrained problem is introduced and a nonlinear programming approach is adopted. Numerical results are provided to show the efficiency and accuracy of our algorithm for both short and long lines.

Suggested Citation

  • Shi, Chuan & Gershwin, Stanley B., 2009. "An efficient buffer design algorithm for production line profit maximization," International Journal of Production Economics, Elsevier, vol. 122(2), pages 725-740, December.
    • Handle: RePEc:eee:proeco:v:122:y:2009:i:2:p:725-740
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    References listed on IDEAS

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    1. Bautista, Joaquin & Pereira, Jordi, 2007. "Ant algorithms for a time and space constrained assembly line balancing problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 2016-2032, March.
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    5. Stanley B. Gershwin & Irvin C. Schick, 1983. "Modeling and Analysis of Three-Stage Transfer Lines with Unreliable Machines and Finite Buffers," Operations Research, INFORMS, vol. 31(2), pages 354-380, April.
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    Cited by:

    1. Guan Wang & Yang Woo Shin & Dug Hee Moon, 2016. "Comparison of three flow line layouts with unreliable machines and profit maximization," Flexible Services and Manufacturing Journal, Springer, vol. 28(4), pages 669-693, December.
    2. Nahas, Nabil & Nourelfath, Mustapha & Gendreau, Michel, 2014. "Selecting machines and buffers in unreliable assembly/disassembly manufacturing networks," International Journal of Production Economics, Elsevier, vol. 154(C), pages 113-126.
    3. Shi, Chuan & Gershwin, Stanley B., 2016. "Part sojourn time distribution in a two-machine line," European Journal of Operational Research, Elsevier, vol. 248(1), pages 146-158.
    4. Przemysław Korytkowski & Tomasz Wiśniewski, 2011. "Performance analysis of commercial offset printing under dynamic priority rules," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 21(1), pages 53-64.
    5. George Liberopoulos, 2020. "Comparison of optimal buffer allocation in flow lines under installation buffer, echelon buffer, and CONWIP policies," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 297-365, June.
    6. Cruz, F.R.B. & Van Woensel, T. & Smith, J. MacGregor, 2010. "Buffer and throughput trade-offs in M/G/1/K queueing networks: A bi-criteria approach," International Journal of Production Economics, Elsevier, vol. 125(2), pages 224-234, June.
    7. Puchkova, Alena & McFarlane, Duncan & Srinivasan, Rengarajan & Thorne, Alan, 2020. "Resilient planning strategies to support disruption-tolerant production operations," International Journal of Production Economics, Elsevier, vol. 226(C).
    8. Patrik Grznár & Milan Gregor & Štefan Mozol & Martin Krajčovič & Ľuboslav Dulina & Martin Gašo & Michal Major, 2019. "A System to Determine the Optimal Work-in-Progress Inventory Stored in Interoperation Manufacturing Buffers," Sustainability, MDPI, vol. 11(14), pages 1-36, July.

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