Functions of Uncertain Variables and Uncertain Programming

摘要

An approach for uncertainty distribution of function of an uncertain variable is established based on uncertain measure. Then expected value of function of an uncertain variable is derived from the distribution. To the sake of computation, uncertain simulations are introduced for approximating the uncertainty distribution, optimistic value and expected value. The simulations are integrated to genetic algorithm for solving uncertain expected value models and uncertain chance-constrained programming models. The efficiency of the proposed methods is shown by some examples.