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Finding Optimal Material Release Times Using Simulation-Based Optimization

Author

Listed:
  • Tito Homem-de-Mello

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205)

  • Alexander Shapiro

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205)

  • Mark L. Spearman

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0205)

Abstract

We present a method for setting release times for jobs with due dates in a stochastic production flow line for which the sequence of jobs has been determined. Unlike other approaches to this problem, ours considers a transient situation. Thus, the flow line will typically contain work in process (WIP), that is, jobs that have been previously released to the system. Our goal is to develop a job release schedule that not only minimizes tardiness but also maximizes flexibility. The philosophy can be characterized as one that seeks to "release as late as possible, but no later!" Our methodology is based on Monte Carlo simulation and consequent optimization by a method that became known as "stochastic counterpart" or "sample path" simulation-based optimization techniques. We use this method to minimize an expected value objective function that contains terms for tardiness and flow time "costs." We include a discussion of how the cost parameters of this objective function can be obtained by considering a "characteristic curve" for the system. We also discuss means for obtaining sensitivity analysis with respect to due dates and service times distributions parameters. We conclude with a numerical example.

Suggested Citation

  • Tito Homem-de-Mello & Alexander Shapiro & Mark L. Spearman, 1999. "Finding Optimal Material Release Times Using Simulation-Based Optimization," Management Science, INFORMS, vol. 45(1), pages 86-102, January.
    • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:1:p:86-102
    DOI: 10.1287/mnsc.45.1.86
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    References listed on IDEAS

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    1. S. Saboo & L. Wang & W. E. Wilhelm, 1989. "Recursion Models for Describing and Managing the Transient Flow of Materials in Generalized Flowlines," Management Science, INFORMS, vol. 35(6), pages 722-742, June.
    2. Uday S. Karmarkar, 1987. "Lot Sizes, Lead Times and In-Process Inventories," Management Science, INFORMS, vol. 33(3), pages 409-418, March.
    3. Mark L. Spearman & Michael A. Zazanis, 1992. "Push and Pull Production Systems: Issues and Comparisons," Operations Research, INFORMS, vol. 40(3), pages 521-532, June.
    4. Uday S. Karmarkar & Sham Kekre & Sunder Kekre & Susan Freeman, 1985. "Lot-Sizing and Lead-time Performance in a Manufacturing Cell," Interfaces, INFORMS, vol. 15(2), pages 1-9, April.
    5. Stephen C. Graves, 1986. "A Tactical Planning Model for a Job Shop," Operations Research, INFORMS, vol. 34(4), pages 522-533, August.
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    Citations

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    Cited by:

    1. Marlin W. Ulmer & Barrett W. Thomas, 2019. "Enough Waiting for the Cable Guy—Estimating Arrival Times for Service Vehicle Routing," Transportation Science, INFORMS, vol. 53(3), pages 897-916, May.
    2. Enlu Zhou & Shalabh Bhatnagar, 2018. "Gradient-Based Adaptive Stochastic Search for Simulation Optimization Over Continuous Space," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 154-167, February.
    3. Song, Dong-Ping, 2006. "Raw material release time control for complex make-to-order products with stochastic processing times," International Journal of Production Economics, Elsevier, vol. 103(1), pages 371-385, September.
    4. William L. Cooper & Tito Homem-de-Mello, 2007. "Some Decomposition Methods for Revenue Management," Transportation Science, INFORMS, vol. 41(3), pages 332-353, August.
    5. Tito Homem-de-Mello & Qingxia Kong & Rodrigo Godoy-Barba, 2022. "A Simulation Optimization Approach for the Appointment Scheduling Problem with Decision-Dependent Uncertainties," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2845-2865, September.
    6. Tito Homem-de-Mello, 2007. "A Study on the Cross-Entropy Method for Rare-Event Probability Estimation," INFORMS Journal on Computing, INFORMS, vol. 19(3), pages 381-394, August.
    7. Wai Kin (Victor) Chan & Lee Schruben, 2008. "Optimization Models of Discrete-Event System Dynamics," Operations Research, INFORMS, vol. 56(5), pages 1218-1237, October.
    8. Johannes Royset, 2013. "On sample size control in sample average approximations for solving smooth stochastic programs," Computational Optimization and Applications, Springer, vol. 55(2), pages 265-309, June.
    9. Tito Homem-de-Mello, 2001. "Estimation of Derivatives of Nonsmooth Performance Measures in Regenerative Systems," Mathematics of Operations Research, INFORMS, vol. 26(4), pages 741-768, November.
    10. Raghu Pasupathy, 2010. "On Choosing Parameters in Retrospective-Approximation Algorithms for Stochastic Root Finding and Simulation Optimization," Operations Research, INFORMS, vol. 58(4-part-1), pages 889-901, August.
    11. Julia Pahl & Stefan Voß & David Woodruff, 2007. "Production planning with load dependent lead times: an update of research," Annals of Operations Research, Springer, vol. 153(1), pages 297-345, September.

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