多目标随机规划逼近问题有效解集的上半收敛性  

The upper semi-convergence of effective solution sets of approximation problems for muiti-objective stochastic programming

作　　者：霍永亮[1,2] 王俊林[2] 周婉娜[2] 

机构地区：[1]重庆文理学院数学与财经学院,数学研究所,重庆永川402160 [2]重庆师范大学数学学院,重庆400047

出　　处：《西北师范大学学报（自然科学版）》2012年第6期22-25,共4页Journal of Northwest Normal University(Natural Science)

基　　金：重庆市教委科研基金资助项目(KJ091211)

摘　　要：在无界且可积函数族对偶的概率测度空间上引入最小信息概率度量,并在初始多目标随机规划问题可行集正则的条件下,利用有效解集的结构特征,给出了多目标随机规划逼近问题有效解集关于最小信息概率度量收敛的上半收敛性条件.This paper introduces minimal information probability metric in duality spaces of unbounded integrable functions family.Under regularity condition of feasible set for original multi-objective stochastic programming problems,a sufficient condition for the upper semi-convergence of approximate effective solution set for multi-objective stochastic programs is given with structure characteristic,when the probability measure sequence is convergence in minimal information probability metric.

关 键 词：多目标随机规划 最小信息概率度量 有效解集 上半收敛性 

分 类 号：O221.5[理学—运筹学与控制论]