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基于CVaR的逼近算法求解一类随机逆变分不等式
CVaR-based formulation and approximation method for a class of stochastic inverse variational inequality problems
【摘要】 随机逆变分不等式是变分不等式领域的重要分支,其被广泛的应用于交通均衡、网络经济均衡、电力系统、物流供应链管理等实际问题.主要工作是通过定义随机逆变分不等式的正则化间隙函数,研究了基于CVaR的一类随机逆变分不等式的逼近算法,并在一定条件下,运用拟蒙特卡洛方法得到这类随机逆变分不等式的解.
【Abstract】 Stochastic inverse variational inequality is an important part of the variational inequalities theory.It is widely applied in traffic equilibrium,network economy equilibrium,electrical power system,logistics management,etc.By defining the regular gap-function,we consider the CVaR-based formulation and approximation method for a class of stochastic inverse variational inequality problems.By employing the quasi-Monte Carlo method,we find a solution of a class of stochastic inverse variational inequality problems under some suitable conditions.
【关键词】 随机逆变分不等式;
基于CVaR;
逼近算法;
正则化间隙函数;
拟蒙特卡洛方法;
【Key words】 stochastic inverse variational inequality; CVaR-based f; formulation and approximation method; regular gap-function; quasi-Monte Carlo method;
【Key words】 stochastic inverse variational inequality; CVaR-based f; formulation and approximation method; regular gap-function; quasi-Monte Carlo method;
【基金】 国家自然科学基金青年科学基金项目(11701480);中央高校基金青年教师项目(2015NZYQN70)
- 【文献出处】 西南民族大学学报(自然科学版) ,Journal of Southwest Minzu University(Natural Science Edition) , 编辑部邮箱 ,2018年03期
- 【分类号】O178
- 【下载频次】68