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Tradeoff Curves, Targeting and Balancing in Manufacturing Queueing Networks

Author

Listed:
  • Gabriel R. Bitran

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

  • Devanath Tirupati

    (The University of Texas at Austin, Austin, Texas)

Abstract

In this paper, we introduce the notions of tradeoff curves, targeting and balancing in manufacturing systems to describe the relationship between variables such as work-in-process, lead-time and capacity. We consider multiproduct manufacturing systems modeled by open networks of queues and formulate the targeting ( TP ) and balancing ( BP ) problems as nonlinear programs. These formulations are based primarily on parametric decomposition methods for estimating performance measures in open queueing networks. Since TP and BP typically are hard to solve, we show that under fairly realistic conditions they can be approximated by easily solvable convex programs. We present heuristics to obtain approximate solutions to these problems and to derive tradeoff curves. We also provide bounds on the performance of the heuristics, relative to the approximation problems, and show that they are asymptotically optimal under mild conditions.

Suggested Citation

  • Gabriel R. Bitran & Devanath Tirupati, 1989. "Tradeoff Curves, Targeting and Balancing in Manufacturing Queueing Networks," Operations Research, INFORMS, vol. 37(4), pages 547-564, August.
  • Handle: RePEc:inm:oropre:v:37:y:1989:i:4:p:547-564
    DOI: 10.1287/opre.37.4.547
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    Citations

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    Cited by:

    1. Patriksson, Michael, 2008. "A survey on the continuous nonlinear resource allocation problem," European Journal of Operational Research, Elsevier, vol. 185(1), pages 1-46, February.
    2. Sinha, Ankur & Das, Arka & Anand, Guneshwar & Jayaswal, Sachin, 2021. "A General Purpose Exact Solution Method for Mixed Integer Concave Minimization Problems," IIMA Working Papers WP 2021-03-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Bretthauer, Kurt M. & Shetty, Bala, 2002. "The nonlinear knapsack problem - algorithms and applications," European Journal of Operational Research, Elsevier, vol. 138(3), pages 459-472, May.
    4. Kurt M. Bretthauer, 2000. "Optimal service and arrival rates in Jackson queueing networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(1), pages 1-17, February.
    5. Sinha, Ankur & Das, Arka & Anand, Guneshwar & Jayaswal, Sachin, 2023. "A general purpose exact solution method for mixed integer concave minimization problems," European Journal of Operational Research, Elsevier, vol. 309(3), pages 977-992.
    6. Parajuli, Anubhuti & Kuzgunkaya, Onur & Vidyarthi, Navneet, 2021. "The impact of congestion on protection decisions in supply networks under disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    7. Simin Huang & Rajan Batta & Rakesh Nagi, 2005. "Distribution network design: Selection and sizing of congested connections," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(8), pages 701-712, December.
    8. Bitran, Gabriel R. & Morabito, Reinaldo., 1995. "An overview of tradeoff curve analysis in the design of manufacturing systems," Working papers 3806-95., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    9. Bretthauer, Kurt M., 1996. "Capacity planning in manufacturing and computer networks," European Journal of Operational Research, Elsevier, vol. 91(2), pages 386-394, June.
    10. Kurt M. Bretthauer & Bala Shetty & Siddhartha Syam, 2003. "A specially structured nonlinear integer resource allocation problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(7), pages 770-792, October.
    11. Elif Akcali & Murray Côté & Chin Lin, 2006. "A network flow approach to optimizing hospital bed capacity decisions," Health Care Management Science, Springer, vol. 9(4), pages 391-404, November.
    12. Papadopoulos, H. T. & Heavey, C., 1996. "Queueing theory in manufacturing systems analysis and design: A classification of models for production and transfer lines," European Journal of Operational Research, Elsevier, vol. 92(1), pages 1-27, July.
    13. Sinha, Ankur & Das, Arka & Anand, Guneshwar & Jayaswal, Sachin, 2021. "A General Purpose Exact Solution Method for Mixed Integer Concave Minimization Problems (revised as on 12/08/2021)," IIMA Working Papers WP 2021-03-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    14. Menezes, Mozart B.C. & Kim, Seokjin & Huang, Rongbing, 2015. "Return-on-investment (ROI) criteria for network design," European Journal of Operational Research, Elsevier, vol. 245(1), pages 100-108.
    15. Ghadimi, Foad & Aouam, Tarik, 2021. "Planning capacity and safety stocks in a serial production–distribution system with multiple products," European Journal of Operational Research, Elsevier, vol. 289(2), pages 533-552.
    16. Wu, Kan & McGinnis, Leon, 2012. "Performance evaluation for general queueing networks in manufacturing systems: Characterizing the trade-off between queue time and utilization," European Journal of Operational Research, Elsevier, vol. 221(2), pages 328-339.
    17. Patriksson, Michael & Strömberg, Christoffer, 2015. "Algorithms for the continuous nonlinear resource allocation problem—New implementations and numerical studies," European Journal of Operational Research, Elsevier, vol. 243(3), pages 703-722.
    18. Kurz, Julian, 2016. "Capacity planning for a maintenance service provider with advanced information," European Journal of Operational Research, Elsevier, vol. 251(2), pages 466-477.
    19. Bretthauer, Kurt M. & Cote, Murray J., 1997. "Nonlinear programming for multiperiod capacity planning in a manufacturing system," European Journal of Operational Research, Elsevier, vol. 96(1), pages 167-179, January.

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