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Analyzing process flexibility: A distribution-free approach with partial expectations

Publication ,  Journal Article
Bidkhori, H; Simchi-Levi, D; Wei, Y
Published in: Operations Research Letters
May 1, 2016

We develop a distribution-free model to evaluate the performance of process flexibility structures when only the mean and partial expectation of the demand are known. We characterize the worst-case demand distribution under general concave objective functions, and apply it to derive tight lower bounds for the performance of chaining structures under the balanced systems (systems with the same number of plants and products). We also derive a simple lower bound for chaining-like structures under unbalanced systems with different plant capacities.

Duke Scholars

Published In

Operations Research Letters

DOI

ISSN

0167-6377

Publication Date

May 1, 2016

Volume

44

Issue

3

Start / End Page

291 / 296

Related Subject Headings

  • Operations Research
  • 4901 Applied mathematics
  • 1503 Business and Management
  • 0103 Numerical and Computational Mathematics
  • 0102 Applied Mathematics
 

Citation

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Bidkhori, H., Simchi-Levi, D., & Wei, Y. (2016). Analyzing process flexibility: A distribution-free approach with partial expectations. Operations Research Letters, 44(3), 291–296. https://doi.org/10.1016/j.orl.2016.02.008
Bidkhori, H., D. Simchi-Levi, and Y. Wei. “Analyzing process flexibility: A distribution-free approach with partial expectations.” Operations Research Letters 44, no. 3 (May 1, 2016): 291–96. https://doi.org/10.1016/j.orl.2016.02.008.
Bidkhori H, Simchi-Levi D, Wei Y. Analyzing process flexibility: A distribution-free approach with partial expectations. Operations Research Letters. 2016 May 1;44(3):291–6.
Bidkhori, H., et al. “Analyzing process flexibility: A distribution-free approach with partial expectations.” Operations Research Letters, vol. 44, no. 3, May 2016, pp. 291–96. Scopus, doi:10.1016/j.orl.2016.02.008.
Bidkhori H, Simchi-Levi D, Wei Y. Analyzing process flexibility: A distribution-free approach with partial expectations. Operations Research Letters. 2016 May 1;44(3):291–296.
Journal cover image

Published In

Operations Research Letters

DOI

ISSN

0167-6377

Publication Date

May 1, 2016

Volume

44

Issue

3

Start / End Page

291 / 296

Related Subject Headings

  • Operations Research
  • 4901 Applied mathematics
  • 1503 Business and Management
  • 0103 Numerical and Computational Mathematics
  • 0102 Applied Mathematics