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Efficient algorithms for buffer space allocation

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  • Stanley Gershwin
  • James Schor

Abstract

This paper describes efficient algorithms for determining how buffer space should be allocated in a flow line. We analyze two problems: a primal problem, which minimizes total buffer space subject to a production rate constraint; and a dual problem, which maximizes production rate subject to a total buffer space constraint. The dual problem is solved by means of a gradient method, and the primal problem is solved using the dual solution. Numerical results are presented. Profit optimization problems are natural generalizations of the primal and dual problems, and we show how they can be solved using essentially the same algorithms. Copyright Kluwer Academic Publishers 2000

Suggested Citation

  • Stanley Gershwin & James Schor, 2000. "Efficient algorithms for buffer space allocation," Annals of Operations Research, Springer, vol. 93(1), pages 117-144, January.
    • Handle: RePEc:spr:annopr:v:93:y:2000:i:1:p:117-144:10.1023/a:1018988226612
    DOI: 10.1023/A:1018988226612
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    Cited by:

    1. Stefan Helber & Katja Schimmelpfeng & Raik Stolletz & Svenja Lagershausen, 2011. "Using linear programming to analyze and optimize stochastic flow lines," Annals of Operations Research, Springer, vol. 182(1), pages 193-211, January.
    2. Chang, Ping-Chen & Lin, Yi-Kuei & Chiang, Yu-Min, 2019. "System reliability estimation and sensitivity analysis for multi-state manufacturing network with joint buffers––A simulation approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 103-109.
    3. Federico Nuñez-Piña & Joselito Medina-Marin & Juan Carlos Seck-Tuoh-Mora & Norberto Hernandez-Romero & Eva Selene Hernandez-Gress, 2018. "Modeling of Throughput in Production Lines Using Response Surface Methodology and Artificial Neural Networks," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    4. G. Alon & D. Kroese & T. Raviv & R. Rubinstein, 2005. "Application of the Cross-Entropy Method to the Buffer Allocation Problem in a Simulation-Based Environment," Annals of Operations Research, Springer, vol. 134(1), pages 137-151, February.
    5. Elisa Gebennini & Andrea Grassi & Cesare Fantuzzi, 2015. "The two-machine one-buffer continuous time model with restart policy," Annals of Operations Research, Springer, vol. 231(1), pages 33-64, August.
    6. Wei, Shuaichong & Nourelfath, Mustapha & Nahas, Nabil, 2023. "Analysis of a production line subject to degradation and preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. 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.
    8. 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.
    9. Colledani, Marcello & Tolio, Tullio, 2009. "Performance evaluation of production systems monitored by statistical process control and off-line inspections," International Journal of Production Economics, Elsevier, vol. 120(2), pages 348-367, August.
    10. Alfieri, Arianna & Matta, Andrea, 2012. "Mathematical programming formulations for approximate simulation of multistage production systems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 773-783.
    11. Kolb, Oliver & Göttlich, Simone, 2015. "A continuous buffer allocation model using stochastic processes," European Journal of Operational Research, Elsevier, vol. 242(3), pages 865-874.
    12. 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.
    13. 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.
    14. Juliane Müller & Christine Shoemaker & Robert Piché, 2014. "SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications," Journal of Global Optimization, Springer, vol. 59(4), pages 865-889, August.
    15. Adrien Wartelle & Farah Mourad-Chehade & Farouk Yalaoui & David Laplanche & Stéphane Sanchez, 2024. "Changing the perspective of system crowding evaluation using a new congestion measure: application to the Emergency Department," Operational Research, Springer, vol. 24(4), pages 1-35, December.
    16. Michael Manitz, 2015. "Analysis of assembly/disassembly queueing networks with blocking after service and general service times," Annals of Operations Research, Springer, vol. 226(1), pages 417-441, March.
    17. Ziwei Lin & Nicla Frigerio & Andrea Matta & Shichang Du, 2021. "Multi-fidelity surrogate-based optimization for decomposed buffer allocation problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 223-253, March.
    18. Nahas, Nabil & Ait-Kadi, Daoud & Nourelfath, Mustapha, 2006. "A new approach for buffer allocation in unreliable production lines," International Journal of Production Economics, Elsevier, vol. 103(2), pages 873-881, October.
    19. Gregory Dobson & Hsiao-Hui Lee & Arvind Sainathan & Vera Tilson, 2012. "A Queueing Model to Evaluate the Impact of Patient "Batching" on Throughput and Flow Time in a Medical Teaching Facility," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 584-599, October.
    20. 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.
    21. Gosavi, Abhijit & Gosavi, Aparna A., 2024. "CONWIP control in the digitized world: The case of the cyber-physical jobshop," International Journal of Production Economics, Elsevier, vol. 270(C).
    22. 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.
    23. Elisa Gebennini & Andrea Grassi & Cesare Fantuzzi & Stanley Gershwin & Irvin Schick, 2013. "Discrete time model for two-machine one-buffer transfer lines with restart policy," Annals of Operations Research, Springer, vol. 209(1), pages 41-65, October.
    24. Sabry Shaaban & Tom Mcnamara & Sarah Hudson, 2015. "The impact of failure, repair and joint imbalance of processing time means & buffer sizes on the performance of unpaced production lines," Post-Print hal-01205567, HAL.
    25. Bengisu Urlu & Nesim K. Erkip, 2020. "Safety stock placement for serial systems under supply process uncertainty," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 395-424, June.

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