Abstract
This paper considers an infinite stage linear decision problem with random coefficients. We assume that the randomness can be defined by a finite Markov chain. Under certain assumptions we are able to calculate an upper bound for the optimal value of the decision problem and to use that bound to determine a useful initial decision.
This research was partially supported by the Office of Naval Research under Contract N00014-69-A-0200-1055 at the University of California and a Research Fellowship at C.O.R.E., Université de Louvain.
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References
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© 1976 The Mathematical Programming Society
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Grinold, R.C. (1976). A new approach to multi-stage stochastic linear programs. In: Wets, R.J.B. (eds) Stochastic Systems: Modeling, Identification and Optimization, II. Mathematical Programming Studies, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0120742
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DOI: https://doi.org/10.1007/BFb0120742
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Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-00786-6
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