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Robust capacity planning in semiconductor manufacturing

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  • Francisco Barahona
  • Stuart Bermon
  • Oktay Günlük
  • Sarah Hood

Abstract

We present a stochastic programming approach to capacity planning under demand uncertainty in semiconductor manufacturing. Given multiple demand scenarios together with associated probabilities, our aim is to identify a set of tools that is a good compromise for all these scenarios. More precisely, we formulate a mixed‐integer program in which expected value of the unmet demand is minimized subject to capacity and budget constraints. This is a difficult two‐stage stochastic mixed‐integer program which cannot be solved to optimality in a reasonable amount of time. We instead propose a heuristic that can produce near‐optimal solutions. Our heuristic strengthens the linear programming relaxation of the formulation with cutting planes and performs limited enumeration. Analyses of the results in some real‐life situations are also presented. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.

Suggested Citation

  • Francisco Barahona & Stuart Bermon & Oktay Günlük & Sarah Hood, 2005. "Robust capacity planning in semiconductor manufacturing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 459-468, August.
    • Handle: RePEc:wly:navres:v:52:y:2005:i:5:p:459-468
    DOI: 10.1002/nav.20086
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    References listed on IDEAS

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    Cited by:

    1. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    2. Smirnov, Dina & van Jaarsveld, Willem & Atan, Zümbül & de Kok, Ton, 2021. "Long-term resource planning in the high-tech industry: Capacity or inventory?," European Journal of Operational Research, Elsevier, vol. 293(3), pages 926-940.
    3. Yang, Jiawei & Li, Yuanyu & Fang, Lei, 2023. "Financing capacity planning with environmental considerations: A non-parametric analysis," Omega, Elsevier, vol. 118(C).
    4. Kai Huang & Shabbir Ahmed, 2009. "The Value of Multistage Stochastic Programming in Capacity Planning Under Uncertainty," Operations Research, INFORMS, vol. 57(4), pages 893-904, August.
    5. Van-Anh Truong & Robin O. Roundy, 2011. "Multidimensional Approximation Algorithms for Capacity-Expansion Problems," Operations Research, INFORMS, vol. 59(2), pages 313-327, April.
    6. John Heiney & Ryan Lovrien & Nicholas Mason & Irfan Ovacik & Evan Rash & Nandini Sarkar & Harry Travis & Zhenying Zhao & Kalani Ching & Shamin Shirodkar & Karl Kempf, 2021. "Intel Realizes $25 Billion by Applying Advanced Analytics from Product Architecture Design Through Supply Chain Planning," Interfaces, INFORMS, vol. 51(1), pages 9-25, February.
    7. Majid Taghavi & Kai Huang, 2020. "A Lagrangian relaxation approach for stochastic network capacity expansion with budget constraints," Annals of Operations Research, Springer, vol. 284(2), pages 605-621, January.
    8. Jian Yang & Jichang Dong & Suixiang Gao & Guoqing Wang, 2023. "Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers," Sustainability, MDPI, vol. 15(6), pages 1-20, March.

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