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Supply capacity acquisition and allocation with uncertain customer demands

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  • Taaffe, Kevin
  • Geunes, Joseph
  • Edwin Romeijn, H.

Abstract

We study a class of capacity acquisition and assignment problems with stochastic customer demands often found in operations planning contexts. In this setting, a supplier utilizes a set of distinct facilities to satisfy the demands of different customers or markets. Our model simultaneously assigns customers to each facility and determines the best capacity level to operate or install at each facility. We propose a branch-and-price solution approach for this new class of stochastic assignment and capacity planning problems. For problem instances in which capacity levels must fall between some pre-specified limits, we offer a tailored solution approach that reduces solution time by nearly 80% over an alternative approach using a combination of commercial nonlinear optimization solvers. We have also developed a heuristic solution approach that consistently provides optimal or near-optimal solutions, where solutions within 0.01% of optimality are found on average without requiring a nonlinear optimization solver.

Suggested Citation

  • Taaffe, Kevin & Geunes, Joseph & Edwin Romeijn, H., 2010. "Supply capacity acquisition and allocation with uncertain customer demands," European Journal of Operational Research, Elsevier, vol. 204(2), pages 263-273, July.
  • Handle: RePEc:eee:ejores:v:204:y:2010:i:2:p:263-273
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    References listed on IDEAS

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    Cited by:

    1. Strinka, Zohar M.A. & Romeijn, H. Edwin & Wu, Jingchen, 2013. "Exact and heuristic methods for a class of selective newsvendor problems with normally distributed demands," Omega, Elsevier, vol. 41(2), pages 250-258.

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