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Technical note ---Linear Inflation Rules for the Random Yield Problem: Analysis and Computations

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  • Woonghee Tim Huh

    (Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027)

  • Mahesh Nagarajan

    (Operations and Logistics Division, Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada)

Abstract

In this paper, we propose a simple heuristic approach for the inventory control problem with stochastic demand and multiplicative random yield. Our heuristic tries to find the best candidate within a class of policies that are referred to in the literature as the linear inflation rule (LIR) policies. Our approach is computationally fast, easy to implement, and intuitive to understand. Moreover, we find that in a significant number of instances our heuristic performs better than several other well-known heuristics that are available in the literature.

Suggested Citation

  • Woonghee Tim Huh & Mahesh Nagarajan, 2010. "Technical note ---Linear Inflation Rules for the Random Yield Problem: Analysis and Computations," Operations Research, INFORMS, vol. 58(1), pages 244-251, February.
    • Handle: RePEc:inm:oropre:v:58:y:2010:i:1:p:244-251
    DOI: 10.1287/opre.1080.0639
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    References listed on IDEAS

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    Cited by:

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    4. Awi Federgruen & Nan Yang, 2014. "Infinite Horizon Strategies for Replenishment Systems with a General Pool of Suppliers," Operations Research, INFORMS, vol. 62(1), pages 141-159, February.
    5. Voelkel, Michael A. & Sachs, Anna-Lena & Thonemann, Ulrich W., 2020. "An aggregation-based approximate dynamic programming approach for the periodic review model with random yield," European Journal of Operational Research, Elsevier, vol. 281(2), pages 286-298.
    6. Xiao, Li & Wang, Ce, 2023. "Multi-location newsvendor problem with random yield: Centralization versus decentralization," Omega, Elsevier, vol. 116(C).
    7. Barιş Ata & Deishin Lee & Erkut Sönmez, 2019. "Dynamic Volunteer Staffing in Multicrop Gleaning Operations," Operations Research, INFORMS, vol. 67(2), pages 295-314, March.
    8. Konstantaras, I. & Skouri, K. & Lagodimos, A.G., 2019. "EOQ with independent endogenous supply disruptions," Omega, Elsevier, vol. 83(C), pages 96-106.
    9. G. P. Kiesmüller & K. Inderfurth, 2018. "Approaches for periodic inventory control under random production yield and fixed setup cost," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(2), pages 449-477, March.
    10. Sonntag, Danja & Kiesmüller, Gudrun P., 2018. "Disposal versus rework – Inventory control in a production system with random yield," European Journal of Operational Research, Elsevier, vol. 267(1), pages 138-149.
    11. Peter Berling & Danja R. Sonntag, 2022. "Inventory control in production–inventory systems with random yield and rework: The unit‐tracking approach," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2628-2645, June.
    12. Saurabh Bansal & Genaro J. Gutierrez & Mahesh Nagarajan, 2021. "Theory-Driven Practical Approach to Integrate R&D and Production Planning for Portfolio Management in Agribusiness," Interfaces, INFORMS, vol. 51(5), pages 332-346, September.
    13. Taesu Cheong & Chelsea White, 2013. "Inventory replenishment control under supply uncertainty," Annals of Operations Research, Springer, vol. 208(1), pages 581-592, September.
    14. Weidong Chen & Cong Shi & Izak Duenyas, 2020. "Optimal Learning Algorithms for Stochastic Inventory Systems with Random Capacities," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1624-1649, July.
    15. Dettenbach, Marcus & Thonemann, Ulrich W., 2015. "The value of real time yield information in multi-stage inventory systems – Exact and heuristic approaches," European Journal of Operational Research, Elsevier, vol. 240(1), pages 72-83.
    16. Robert N. Boute & Stephen M. Disney & Joren Gijsbrechts & Jan A. Van Mieghem, 2022. "Dual Sourcing and Smoothing Under Nonstationary Demand Time Series: Reshoring with SpeedFactories," Management Science, INFORMS, vol. 68(2), pages 1039-1057, February.

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