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Solution of a Product Substitution Problem Using Stochastic Programming

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Probabilistic Constrained Optimization

Part of the book series: Nonconvex Optimization and Its Applications ((NOIA,volume 49))

Abstract

Stochastic programming models of optical fiber production planning are presented. The purpose is to set the optimal fiber manufacturing goals while accounting for the uncertainty primarily in the yield and secondly in the demand. The model is solved for the case when the data follows a multivariate discrete distribution, and also for the case of a multivariate normal distribution, which is used to approximate the discrete data.

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Author information

Authors and Affiliations

  1. Lucent Technologies, Princeton, New Jersey, USA

    Michael R. Murr

  2. Rutgers University, New Brunswick, New Jersey, USA

    András Prékopa

Authors
  1. Michael R. Murr
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  2. András Prékopa
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Editor information

Editors and Affiliations

  1. University of Florida, Gainesville, Florida, USA

    Stanislav P. Uryasev

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© 2000 Springer Science+Business Media Dordrecht

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Murr, M.R., Prékopa, A. (2000). Solution of a Product Substitution Problem Using Stochastic Programming. In: Uryasev, S.P. (eds) Probabilistic Constrained Optimization. Nonconvex Optimization and Its Applications, vol 49. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3150-7_14

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  • DOI: https://doi.org/10.1007/978-1-4757-3150-7_14

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-4840-3

  • Online ISBN: 978-1-4757-3150-7

  • eBook Packages: Springer Book Archive

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