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Keywords:
multistage stochastic programming problem; individual probability constraints; autoregressive sequence; Wasserstein metric; empirical estimates; multiobjective problems
multistage stochastic programming problem; individual probability constraints; autoregressive sequence; Wasserstein metric; empirical estimates; multiobjective problems
Summary:
The paper deals with a special case of multistage stochastic programming problems. In particular, the paper deals with multistage stochastic programs in which a random element follows an autoregressive sequence and constraint sets correspond to the individual probability constraints. The aim is to investigate a stability (considered with respect to a probability measures space) and empirical estimates. To achieve new results the Wasserstein metric determined by ${\cal L}_{1}$ norm and results of multiobjective optimization theory are employed.
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