Multistage stochastic programs via autoregressive sequences and individual probability constraints
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 L-1 norm and results of multiobjective optimization theory are employed.
autoregressive sequence individual probability constraints multistage stochastic programming problem empirical estimates wasserstein metric multiobjective problems