Projected Trust Region Method for Stochastic Tensor Absolute Value Equations with Discrete Distribution

In this paper, a kind of stochastic tensor absolute value equations with discrete distribution is considered. Using the expected value method in the discrete probability space, we transform it into a minimization problem with non-negative constraints. To solve this constrained optimization problem, we develop a projected trust region method which combines the quasi-Newton method with the trust region method. And the convergence result is also established under mild conditions. Finally, we present some numerical experiments to illustrate the effectiveness of our method.