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A general strategic capacity planning model under demand uncertainty

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  • Woonghee Tim Huh
  • Robin O. Roundy
  • Metin Çakanyildirim

Abstract

Capacity planning decisions affect a significant portion of future revenue. In equipment intensive industries, these decisions usually need to be made in the presence of both highly volatile demand and long capacity installation lead times. For a multiple product case, we present a continuous‐time capacity planning model that addresses problems of realistic size and complexity found in current practice. Each product requires specific operations that can be performed by one or more tool groups. We consider a number of capacity allocation policies. We allow tool retirements in addition to purchases because the stochastic demand forecast for each product can be decreasing. We present a cluster‐based heuristic algorithm that can incorporate both variance reduction techniques from the simulation literature and the principles of a generalized maximum flow algorithm from the network optimization literature. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006

Suggested Citation

  • Woonghee Tim Huh & Robin O. Roundy & Metin Çakanyildirim, 2006. "A general strategic capacity planning model under demand uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(2), pages 137-150, March.
    • Handle: RePEc:wly:navres:v:53:y:2006:i:2:p:137-150
    DOI: 10.1002/nav.20128
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    References listed on IDEAS

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    1. Metin Çakanyıldırım & Robin O. Roundy & Samuel C. Wood, 2004. "Optimal machine capacity expansions with nested limitations under stochastic demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(2), pages 217-241, March.
    2. Woonghee Tim Huh & Robin O. Roundy, 2005. "A continuous‐time strategic capacity planning model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(4), pages 329-343, June.
    3. Sarah M. Ryan, 2003. "Capacity expansion with lead times and autocorrelated random demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(2), pages 167-183, March.
    4. Sarah M. Ryan, 2004. "Capacity Expansion for Random Exponential Demand Growth with Lead Times," Management Science, INFORMS, vol. 50(6), pages 740-748, June.
    5. Stuart Bermon & Sarah Jean Hood, 1999. "Capacity Optimization Planning System (CAPS)," Interfaces, INFORMS, vol. 29(5), pages 31-50, October.
    6. Shabbir Ahmed & Nikolaos V. Sahinidis, 2003. "An Approximation Scheme for Stochastic Integer Programs Arising in Capacity Expansion," Operations Research, INFORMS, vol. 51(3), pages 461-471, June.
    7. John R. Birge, 2000. "Option Methods for Incorporating Risk into Linear Capacity Planning Models," Manufacturing & Service Operations Management, INFORMS, vol. 2(1), pages 19-31, August.
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    1. Li, Xishu & Zuidwijk, Rob & de Koster, M.B.M, 2023. "Optimal competitive capacity strategies: Evidence from the container shipping market," Omega, Elsevier, vol. 115(C).
    2. Hongmin Li & Stephen C. Graves & Woonghee Tim Huh, 2014. "Optimal Capacity Conversion for Product Transitions Under High Service Requirements," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 46-60, February.
    3. Chien, Chen-Fu & Wu, Cheng-Hung & Chiang, Yu-Shian, 2012. "Coordinated capacity migration and expansion planning for semiconductor manufacturing under demand uncertainties," International Journal of Production Economics, Elsevier, vol. 135(2), pages 860-869.
    4. Yi Yang & Youhua (Frank) Chen & Yun Zhou, 2014. "Coordinating Inventory Control and Pricing Strategies Under Batch Ordering," Operations Research, INFORMS, vol. 62(1), pages 25-37, February.
    5. Li, X. & Zuidwijk, R.A. & de Koster, M.B.M. & Dekker, R., 2016. "Competitive Capacity Investment under Uncertainty," ERIM Report Series Research in Management ERS-2016-005-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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