Abstract：This paper studied the convergence of approximate solutions for stochastic programming and proved that any optimum solution sequence of corresponding problems will converge to one of the optimum solutions of the original problem if random vector sequence {Y( k )(k) } converges to Y(k) in distribution. These results provide the theoretical foundation for constructing approximate algorithms.
骆建文,鲁世杰. 随机规划逼近解的收敛性[J]. 浙江大学学报（理学版）, 2000, 27(5): 493-497.
LUO Jian-wen, LU Shi-jie. Convergence of approximate solutions in stochastic programming.. Journal of ZheJIang University(Science Edition), 2000, 27(5): 493-497.
