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Titlebook: Duality in Stochastic Linear and Dynamic Programming; Willem K. Klein Haneveld Book 1986 Springer-Verlag Berlin Heidelberg 1986 dynamic pr

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On the Behaviour of the Optimal Value Operator of Dynamic Programming,s to minimize the expected costs, summed over all stages. For details on the SDP problem we refer the reader to Section 4.6. There we gave also a formal definition of a “policy”; a policy may be seen as a complete specification of all particular choices which possibly are made by the decision maker at any stage and at any state.
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Jazz,lution depends heavily on the value of some inaccurate data, it might be sensible to take the uncertainty of the coefficients into consideration in a more fundamental way. Since an evident framework for the quantitative analysis of uncertainty is provided by probability theory it seems only natural
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Tiziana Calamoneri,Blerina Sinaimeri CCP problems may be nonconvex whereas SPR problems are always convex [5 page 90]. Even if mathematical equivalence can be established there still are differences between CCP and SPR models which might be important for the model builder.
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Stochastic Linear Programming Models,lution depends heavily on the value of some inaccurate data, it might be sensible to take the uncertainty of the coefficients into consideration in a more fundamental way. Since an evident framework for the quantitative analysis of uncertainty is provided by probability theory it seems only natural
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Stochastic Linear Programming Models,bvious: many practical problems can be modeled, at least approximately, as linear programs, and powerful software is available. Nevertheless, even if the problem has the necessary linear structure it is not sure that the linear programming approach works. One of the reasons is that the model builder
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