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求解一类随机混合互补问题的抽样平均逼近方法

发表时间:2011-07-15  浏览量:1429  下载量:641
全部作者: 何志峰,林贵华
作者单位: 大连理工大学数学科学学院
摘 要: 研究一类随机混合互补问题(stochastic mixed complementarity problem,SMCP)。首先利用Fischer-Burmeister函数将随机混合互补问题转化为一个非光滑方程组,然后利用基于蒙特卡罗方法的抽样平均逼近方法并结合半光滑牛顿法求解该方程组,并给出相关的收敛性分析。最后,将该方法应用到交通均衡问题中,并进行简单的数值实验。
关 键 词: 非线性规划;随机混合互补问题;抽样平均逼近;半光滑牛顿法;蒙特卡罗方法;交通均衡问题
Title: Sample average approximation method for solving a class of stochastic mixed complementarity problems
Author: HE Zhifeng, LIN Guihua
Organization: School of Mathematical Sciences, Dalian University of Technology
Abstract: In this paper, a class of stochastic mixed complementarity problems (SMCP) is considered. The Fischer-Burmeister function is used to reformulate the SMCP as nonsmooth equations. Then, the sampling average approximation techniques based on Monte Carlo method are employed to propose a semismooth Newton method for solving the equations. Convergence analysis is given as well. The results are finally applied to traffic equilibrium problems and some preliminary numerical results are reported.
Key words: nonlinear programming; stochastic mixed complementarity problem; sample average approximation; semismooth Newton method; Monte Carlo method; traffic equilibrium problem
发表期数: 2011年7月第13期
引用格式: 何志峰,林贵华. 求解一类随机混合互补问题的抽样平均逼近方法[J]. 中国科技论文在线精品论文,2011,4(13):1155-1162.
 
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