作　　者： ; ; ;

机构地区： 华南理工大学

出　　处： 《青岛科技大学学报（自然科学版）》 2004年第5期402-405,414,共5页

摘　　要： 基于两阶段随机规划的求解问题对不确定条件过程优化是十分重要的,本研究将蒙特卡罗积分策略与基于对偶理论的可行域限定条件相结合提出了改进算法,同时还提出了两阶段随机规划改进算法中确定有效抽样点数的方法,算例证明了该算法的有效性以及确定有效抽样点数判据的可行性。 It is important to study process optimization under uncertainty based on 2-stages stochastic linear programs. An improved algorithm of the former work for process optimization under uncertainty based on 2-stages stochastic linear programs is proposed, the key feature of our approach is combined Monte Carlo sampling with feasibility cuts based on dual theory. A method of getting efficacious samples number in our improved algorithm is also proposed in this paper. On the problems tested, the improved algorithm and the criterion of efficacious samples numbers are realistic.

关 键 词： 蒙特卡罗积分策略 随机规划 有效抽样点数 不确定参数 多变性 求解算法

领　　域： [化学工程]