An approximating algorithm for compensated bi-level stochastic programming.

For the purpose of transforming a bi-level compensated stochastic programming to a deterministic optimization problem, the experience mean approximation method is used in this paper. A numerical example and its solution analysis show that this method do d not require to understand the distribution of the related random variable, thereby reducing the solving difficulty. [ABSTRACT FROM AUTHOR]