随机变分不等式的二阶微分方程方法

庄慧婷, 王莉, 孙菊贺, 贾丹娜, 袁艳红

沈阳航空航天大学学报 ›› 2023, Vol. 40 ›› Issue (4) : 88 -96.

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沈阳航空航天大学学报 ›› 2023, Vol. 40 ›› Issue (4) : 88 -96. DOI: 10.3969/j.issn.2095-1248.2023.04.012
基础科学和工程

随机变分不等式的二阶微分方程方法

    庄慧婷1(), 王莉1(), 孙菊贺1, 贾丹娜1, 袁艳红2
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Second-order differential equation method for solving stochastic variational inequality

    ZHUANG Huiting1(), WANG Li1(), SUN Juhe1, JIA Danna1, YUAN Yanhong2
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摘要

运用具有正黏性阻尼系数和时间尺度系数的二阶微分方程系统来求解随机变分不等式问题(stochastic variational inequality problem,SVIP)。首先,应用互补函数和样本均值近似(sample average approximation, SAA)方法对原始问题进行等价转换,即将随机变分不等式问题转化为一个方程组,在此基础上建立具有正黏性阻尼系数 γ t和时间尺度系数 β t的二阶微分方程系统;其次,研究了该二阶微分方程系统轨迹的收敛性和收敛速率;最后,给出两个数值实验说明该二阶微分方程系统求解随机变分不等式问题的有效性。

Abstract

A system of second-order differential equation with positive viscous damping coefficients and time-scale coefficients was applied to solve the stochastic variational inequality problem (SVIP). Firstly, the complementary function and the sample average approximation (SAA) method were applied to equate the original problem, and the stochastic variational inequality problem was transformed into a system of equations. Based on this, a second-order differential equation system with positive viscous damping coefficients γ t and time-scale coefficients β t was established. Secondly, the convergence and convergence rate of the trajectory of the second-order differential equation system were obtained. Finally, two numerical experiments were presented to demonstrate the effectiveness of the second-order differential equation system in solving stochastic variational inequality problems.

关键词

随机变分不等式 / 二阶微分方程 / 互补函数 / 样本均值近似方法 / 凸优化问题

Key words

stochastic variational inequality / second-order differential equation / complementary function / sample average approximation method / convex optimization problem

引用本文

引用格式 ▾
庄慧婷, 王莉, 孙菊贺, 贾丹娜, 袁艳红. 随机变分不等式的二阶微分方程方法[J]. 沈阳航空航天大学学报, 2023, 40(4): 88-96 DOI:10.3969/j.issn.2095-1248.2023.04.012

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参考文献

1
Thong D V Hieu D V.Weak and strong convergence theorems for variational inequality problems [J].Numerical Algorithms201878(4):1045-1060.
2
Wu Z L Lu Y.Minimum and maximum principle sufficiency for a nonsmooth variational inequality [J].Bulletin of the Malaysian Mathematical Sciences Society202144(3):1233-1257.
3
Nnakwe M O.An algorithm for approximating a common solution of variational inequality and convex minimization problems[J].Optimization202170(10):2227-2246.
4
Jolaoso L O Taiwo A Alakoya T O,et al.A unified algorithm for solving variational inequality and fixed point problems with application to the split equality problem [J].Computational and Applied Mathematics202039(1):1-28.
5
Eslamian M.Variational inequality over the set of common solutions of a system of bilevel variational inequality problem with applcations [J].Revista de la Real Academia de Ciencias Exactas,Físicas y Naturales.Serie A.Matemáticas,2022116(1):1-18.
6
Parise F Ozdaglar A.A variational inequality framework for network games:existence,uniqueness,convergence and sensitivity analysis [J].Games Economic Behavior2019114(13):47-82.
7
杨振平.随机变分不等式问题及其在天然气市场中的应用研究[D].上海:上海大学,2019.
8
陈琦琼.不确定变分不等式及其在非合作博弈中的应用[D].南京:南京理工大学,2018.
9
Ferguson A R Dantzig G B.The allocation of aircraft to routes-an example of linear programming under uncertain demand [J].Management Science19563(1):45-73.
10
R.Tyrrell Rockafellar and Roger J-B Wets.Stochastic variational inequalities:single-stage to multistage [J].Mathematical Programming2017165(1):331-360.
11
Harker P T.A variational inequality approach for the determination of oligopolistic market equilibrium [J].Mathematical Programming198430(1):105-111.
12
Shapiro A Dentcheva D Ruszczynski A.Lectures on Stochastic Programming:Modeling and Theory [M].Philadeslphia:Society for Industrial and Applied Mathematics,2021.
13
Zhao Y Zhang J Yang X M,et al.Expected residual minimization formulation for a class of stochastic vector variational inequalities [J].Journal of Optimization Theory and Applications2017175(2):545-566.
14
Chen S Pang L P Ma X F,et al.SAA method based on modified Newton method for stochastic variational inequality with second-order cone constraints and application in portfolio optimization [J].Mathematical Methods of Operations Research201684(1):129-154.
15
Sun J H Chen J S Ko C H.Neural networks for solving second-order cone constrained variational inequality problem [J].Computational Optimization and Applications201051(2):623-648.
16
Facchinei F Pang J S.Finite-Dimensional Variational Inequalities and Complementarity Problems[M].New York:Springer-Verlag,2003.
17
Attouch H Chbani Z Riahi H,Fast convex optimization via a third-order in time evolution equation [J].Optimization202071(5):1275-1304.
18
Wang C M He S X Wu H Y.An implementable SAA nonlinear lagrange algorithm for constrained minimax stochastic optimization problems[J].Mathematical Problems in Engineering2018(16):1-13.
19
Lam H Jiang G X Fu M C,et al.On efficiencies of stochastic optimization procedures under importance sampling [C] //Winter Simulation Conference Proceedings.Gothenburg,Sweden,2018,1862-1873.

基金资助

国家自然科学基金(11901422)

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