Multi-objective stochastic programming problems correspond to economic situations in which economic process is simultaneously influenced by a random environment and a decision parameter selected with respect to multi-objective optimization problem depending on the probability measure.
Economic and financial activities are often influenced simultaneously by a decision and random factors. Since the decision parameter must be constructed mostly without knowledge of a random element realization, an optimization problem depending on a probability measure corresponds to this situation. Usually in applications this measure must be replaced by an empirical one.
In the grant project, first, we intend to construct models of economic activities. Furthermore, we focus on a construction of approximate solution schemes of the corresponding optimization problems. Of course, to this end, an investigation of the models will be necessary.
Economic and social phenomena develop over time, they are mostly influenced by random factors and, moreover, it is necessary very often to evaluate them simultaneously by several "utility" functions. Consequently, construction of the corresponding mathematical models is generally complicated.