On game approach tо solving of one stochastic programming problem

The paper is concerned with a long term stochastic programming problem [1]. Algorithms are proposed for finding the saddle point of the Lagrange function which are stochastic analog of the well-known Arrow — Hurwitz algorithm and based on the ideas of generalized gradient, stochastic approximation and regularization methods. The convergence of these algorithms with probability one and in the mean square sense is proved. The model constructing problem for the «average» consumer is considered as an example.