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Robustness Against Dependence in Pert

  • Chapter
Duality in Stochastic Linear and Dynamic Programming

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 274))

Abstract

A typical minimax model of stochastic programming can be described as minimizeT∈T,supH∈H EHf (T, ξ). Here T is a vector of decision variables, restricted to a fixed feasible set T ⊂ ℝ N. The function f to be minimized depends not only on T but also on the unknown realization of an n-dimensional random vector ξ. For that reason the expected value of f is chosen as the objective function. However, the distribution function H of ξ is not completely known to the decision maker: it may be any element of a family H of distribution functions. The supremization in the “inner problem” indicates that a worst-case approach is adopted: the decision on T in the “outer problem” is based on the most unfavorable distributions in H

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Authors and Affiliations

  1. Institute of Econometrics, University of Groningen, P.O. Box 800, 9700 AV, Groningen, The Netherlands

    Dr. Willem K. Klein Haneveld

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  1. Dr. Willem K. Klein Haneveld
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© 1986 Springer-Verlag Berlin Heidelberg

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Klein Haneveld, W.K. (1986). Robustness Against Dependence in Pert. In: Duality in Stochastic Linear and Dynamic Programming. Lecture Notes in Economics and Mathematical Systems, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-51697-9_7

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  • DOI: https://doi.org/10.1007/978-3-642-51697-9_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-16793-8

  • Online ISBN: 978-3-642-51697-9

  • eBook Packages: Springer Book Archive

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