
Previous Article
Improved convergence properties of the LinFukushimaRegularization method for mathematical programs with complementarity constraints
 NACO Home
 This Issue

Next Article
Recent advances in numerical methods for nonlinear equations and nonlinear least squares
CVaRbased formulation and approximation method for stochastic variational inequalities
1.  Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China 
2.  School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China 
References:
[1] 
R. P. Agdeppa, N. Yamashita and M. Fukushima, Convex expected residual models for stochastic affine variational inequality problems and its application to the traffic equilibrium problem, Pacific Journal of Optimization, 6 (2010), 319. 
[2] 
P. Artzner, F. Delbaen, J. M. Eber and D. Heath, Coherent measures of risk, Mathematical Finance, 9 (1999), 203228. doi: 10.1111/14679965.00068. 
[3] 
S. Boyd and L. Vandenberghe, "Convex Optimization," Cambridge University Press, Cambridge, 2004. 
[4] 
C. Chen and O. L. Mangasarian, A class of smoothing functions for nonlinear and mixed complementarity problems, Computational Optimization and Applications, 5 (1996), 97138. doi: 10.1007/BF00249052. 
[5] 
X. Chen and M. Fukushima, Expected residual minimization method for stochastic linear complementarity problems, Mathematics of Operations Research, 30 (2005), 10221038. doi: 10.1287/moor.1050.0160. 
[6] 
X. Chen, C. Zhang and M. Fukushima, Robust solution of monotone stochastic linear complementarity problems, Mathematical Programming, 117 (2009), 5180. doi: 10.1007/s101070070163z. 
[7] 
R. W. Cottle, J. S. Pang and R. E. Stone, "The Linear Complementarity Problem," Academic Press, New York, 1992. 
[8] 
F. Facchinei and J. S. Pang, "FiniteDimensional Variational Inequalities and Complementarity Problems," SpringerVerlag, New York, 2003. 
[9] 
H. Fang, X. Chen and M. Fukushima, Stochastic R$_0$ matrix linear complementarity problems, SIAM Journal on Optimization, 18 (2007), 482506. doi: 10.1137/050630805. 
[10] 
M. Fukushima, Equivalent differentiable optimization problems and descent methods for asymmetric variational inequality problems, Mathematical Programming, 53 (1992), 99110. doi: 10.1007/BF01585696. 
[11] 
M. Fukushima, Merit functions for variational inequality and complementarity problems, in "Nonlinear Optimization and Applications"(eds. G. Di Pillo and F. Giannessi), Plenum Press, New York, 1996, 155170. 
[12] 
G. Gürkan, A. Y. Özge and S. M. Robinson, Samplepath solution of stochastic variational inequalities, Mathematical Programming, 84 (1999), 313333. doi: 10.1007/s101070050024. 
[13] 
P. T. Harker and J. S. Pang, Finitedimensional variational inequality and nonlinear complementarity problems: A survey of theory, algorithms and applications, Mathematical Programming, 48 (1990), 161220. doi: 10.1007/BF01582255. 
[14] 
W. W. Hogan, Pointtoset maps in mathematical programming, SIAM Review, 15 (1973), 591603. doi: 10.1137/1015073. 
[15] 
H. Jiang and H. Xu, Stochastic approximation approaches to the stochastic variational inequality problem, IEEE Transactions on Automatic Control, 53 (2008), 14621475. doi: 10.1109/TAC.2008.925853. 
[16] 
I. V. Konnov, "Equilibrium Models and Variational Inequalities," Elsevier, Amsterdam, 2007. 
[17] 
D. Kinderlehrer and G. Stampacchia, "An Introduction to Variational Inequalities and Their Applications," Academic Press, New York, 1980. 
[18] 
T. Larsson and M. Patriksson, A class of gap functions for variational inequalities, Mathematical Programming, 64 (1994), 5379. doi: 10.1007/BF01582565. 
[19] 
G. H. Lin, Combined Monte Carlo sampling and penalty method for stochastic nonlinear complementarity problems, Mathematics of Computation, 78 (2009), 16711686. doi: 10.1090/S0025571809022066. 
[20] 
G. H. Lin, X. Chen and M. Fukushima, New restricted NCP function and their applications to stochastic NCP and stochastic MPEC, Optimization, 56 (2007), 641753. doi: 10.1080/02331930701617320. 
[21] 
G. H. Lin and M. Fukushima, New reformulations for stochastic complementarity problems, Optimization Methods and Software, 21 (2006), 551564. doi: 10.1080/10556780600627610. 
[22] 
G. H. Lin and M. Fukushima, Stochastic equilibrium problems and stochastic mathematical programs with equilibrium constraints: A survey, Pacific Journal of Optimization, 6 (2010), 455482. 
[23] 
C. Ling, L. Qi, G. Zhou and L. Caccetta, The $SC^1$ property of an expected residual function arising from stochastic complementarity problems, Operations Research Letters, 36 (2008), 456460. doi: 10.1016/j.orl.2008.01.010. 
[24] 
M. J. Luo and G. H. Lin, Expected residual minimization method for stochastic variational inequality problems, Journal of Optimization Theory and Application, 140 (2009), 103116. doi: 10.1007/s1095700894396. 
[25] 
M. J. Luo and G. H. Lin, Convergence results of the ERM method for nonlinear stochastic variational inequality problems, Journal of Optimization Theory and Application, 142 (2009), 569581. doi: 10.1007/s1095700995343. 
[26] 
M. J. Luo and G. H. Lin, Stochastic variational inequality problems with additional constraints and their applications in supply chain network equilibria,, Pacific Journal of Optimization, (). 
[27] 
J. S. Pang, Complementarity problems, in "Handbook in Global Optimization"}(eds. R. Horst and P. Pardalos, Kluwer Academic Publishers, Boston, 1994. 
[28] 
J. M. Peng, Convexity of the implicit Lagrangian, Journal of Optimization Theory and Applications, 92 (1997), 331341. doi: 10.1023/A:1022607213765. 
[29] 
R. T. Rockafellar and S. Uryasev, Conditional valueatrisk for general loss distributions, Journal of Banking and Finance, 26 (2002), 14431471. doi: 10.1016/S03784266(02)002716. 
[30] 
R. T. Rockafellar and R. J. B. Wets, "Variational Analysis," Springer, Berlin, 1998. doi: 10.1007/9783642024313. 
[31] 
R. T. Rockafellar and S. Uryasev, Optimization of conditional valueatrisk, Journal of Risk, 2 (2000), 493517. 
[32] 
A. Ruszczynski and A. Shapiro, "Stochastic Programming, Handbooks in Operations Research and Management Science," Elsevier, 2003. 
[33] 
H. Xu, Sample average approximation methods for a class of stochastic variational inequality problems, AsiaPacific Journal of Operations Research, 27 (2010), 103119. 
[34] 
H. Xu and D. Zhang, Smooth sample average approximation of stationary points in nonsmooth stochastic optimization and applications, Mathematical Programming, 119 (2009), 371401. doi: 10.1007/s1010700802140. 
[35] 
N. Yamashita, K. Taji and M. Fukushima, Unconstrained optimization reformulations of variational inequality problems, Journal of Optimization Theory and Applications, 92 (1997), 439456. doi: 10.1023/A:1022660704427. 
[36] 
C. Zhang and X. Chen, Stochastic nonlinear complementarity problem and applications to traffic equilibrium under uncertainty, Journal of Optimization Theory and Applications, 137 (2008), 277295. doi: 10.1007/s1095700893586. 
[37] 
C. Zhang, X. Chen and A. Sumalee, Robust Wardrops user equilibrium assignment under stochastic demand and supply: expected residual minimization approach, Transportation Research Part B, 2010 (Online first). 
[38] 
G. L. Zhou and L. Caccetta, Feasible semismooth Newton method for a class of stochastic linear complementarity problems, Journal of Optimization Theory and Applications, 139 (2008), 379392. doi: 10.1007/s1095700894062. 
show all references
References:
[1] 
R. P. Agdeppa, N. Yamashita and M. Fukushima, Convex expected residual models for stochastic affine variational inequality problems and its application to the traffic equilibrium problem, Pacific Journal of Optimization, 6 (2010), 319. 
[2] 
P. Artzner, F. Delbaen, J. M. Eber and D. Heath, Coherent measures of risk, Mathematical Finance, 9 (1999), 203228. doi: 10.1111/14679965.00068. 
[3] 
S. Boyd and L. Vandenberghe, "Convex Optimization," Cambridge University Press, Cambridge, 2004. 
[4] 
C. Chen and O. L. Mangasarian, A class of smoothing functions for nonlinear and mixed complementarity problems, Computational Optimization and Applications, 5 (1996), 97138. doi: 10.1007/BF00249052. 
[5] 
X. Chen and M. Fukushima, Expected residual minimization method for stochastic linear complementarity problems, Mathematics of Operations Research, 30 (2005), 10221038. doi: 10.1287/moor.1050.0160. 
[6] 
X. Chen, C. Zhang and M. Fukushima, Robust solution of monotone stochastic linear complementarity problems, Mathematical Programming, 117 (2009), 5180. doi: 10.1007/s101070070163z. 
[7] 
R. W. Cottle, J. S. Pang and R. E. Stone, "The Linear Complementarity Problem," Academic Press, New York, 1992. 
[8] 
F. Facchinei and J. S. Pang, "FiniteDimensional Variational Inequalities and Complementarity Problems," SpringerVerlag, New York, 2003. 
[9] 
H. Fang, X. Chen and M. Fukushima, Stochastic R$_0$ matrix linear complementarity problems, SIAM Journal on Optimization, 18 (2007), 482506. doi: 10.1137/050630805. 
[10] 
M. Fukushima, Equivalent differentiable optimization problems and descent methods for asymmetric variational inequality problems, Mathematical Programming, 53 (1992), 99110. doi: 10.1007/BF01585696. 
[11] 
M. Fukushima, Merit functions for variational inequality and complementarity problems, in "Nonlinear Optimization and Applications"(eds. G. Di Pillo and F. Giannessi), Plenum Press, New York, 1996, 155170. 
[12] 
G. Gürkan, A. Y. Özge and S. M. Robinson, Samplepath solution of stochastic variational inequalities, Mathematical Programming, 84 (1999), 313333. doi: 10.1007/s101070050024. 
[13] 
P. T. Harker and J. S. Pang, Finitedimensional variational inequality and nonlinear complementarity problems: A survey of theory, algorithms and applications, Mathematical Programming, 48 (1990), 161220. doi: 10.1007/BF01582255. 
[14] 
W. W. Hogan, Pointtoset maps in mathematical programming, SIAM Review, 15 (1973), 591603. doi: 10.1137/1015073. 
[15] 
H. Jiang and H. Xu, Stochastic approximation approaches to the stochastic variational inequality problem, IEEE Transactions on Automatic Control, 53 (2008), 14621475. doi: 10.1109/TAC.2008.925853. 
[16] 
I. V. Konnov, "Equilibrium Models and Variational Inequalities," Elsevier, Amsterdam, 2007. 
[17] 
D. Kinderlehrer and G. Stampacchia, "An Introduction to Variational Inequalities and Their Applications," Academic Press, New York, 1980. 
[18] 
T. Larsson and M. Patriksson, A class of gap functions for variational inequalities, Mathematical Programming, 64 (1994), 5379. doi: 10.1007/BF01582565. 
[19] 
G. H. Lin, Combined Monte Carlo sampling and penalty method for stochastic nonlinear complementarity problems, Mathematics of Computation, 78 (2009), 16711686. doi: 10.1090/S0025571809022066. 
[20] 
G. H. Lin, X. Chen and M. Fukushima, New restricted NCP function and their applications to stochastic NCP and stochastic MPEC, Optimization, 56 (2007), 641753. doi: 10.1080/02331930701617320. 
[21] 
G. H. Lin and M. Fukushima, New reformulations for stochastic complementarity problems, Optimization Methods and Software, 21 (2006), 551564. doi: 10.1080/10556780600627610. 
[22] 
G. H. Lin and M. Fukushima, Stochastic equilibrium problems and stochastic mathematical programs with equilibrium constraints: A survey, Pacific Journal of Optimization, 6 (2010), 455482. 
[23] 
C. Ling, L. Qi, G. Zhou and L. Caccetta, The $SC^1$ property of an expected residual function arising from stochastic complementarity problems, Operations Research Letters, 36 (2008), 456460. doi: 10.1016/j.orl.2008.01.010. 
[24] 
M. J. Luo and G. H. Lin, Expected residual minimization method for stochastic variational inequality problems, Journal of Optimization Theory and Application, 140 (2009), 103116. doi: 10.1007/s1095700894396. 
[25] 
M. J. Luo and G. H. Lin, Convergence results of the ERM method for nonlinear stochastic variational inequality problems, Journal of Optimization Theory and Application, 142 (2009), 569581. doi: 10.1007/s1095700995343. 
[26] 
M. J. Luo and G. H. Lin, Stochastic variational inequality problems with additional constraints and their applications in supply chain network equilibria,, Pacific Journal of Optimization, (). 
[27] 
J. S. Pang, Complementarity problems, in "Handbook in Global Optimization"}(eds. R. Horst and P. Pardalos, Kluwer Academic Publishers, Boston, 1994. 
[28] 
J. M. Peng, Convexity of the implicit Lagrangian, Journal of Optimization Theory and Applications, 92 (1997), 331341. doi: 10.1023/A:1022607213765. 
[29] 
R. T. Rockafellar and S. Uryasev, Conditional valueatrisk for general loss distributions, Journal of Banking and Finance, 26 (2002), 14431471. doi: 10.1016/S03784266(02)002716. 
[30] 
R. T. Rockafellar and R. J. B. Wets, "Variational Analysis," Springer, Berlin, 1998. doi: 10.1007/9783642024313. 
[31] 
R. T. Rockafellar and S. Uryasev, Optimization of conditional valueatrisk, Journal of Risk, 2 (2000), 493517. 
[32] 
A. Ruszczynski and A. Shapiro, "Stochastic Programming, Handbooks in Operations Research and Management Science," Elsevier, 2003. 
[33] 
H. Xu, Sample average approximation methods for a class of stochastic variational inequality problems, AsiaPacific Journal of Operations Research, 27 (2010), 103119. 
[34] 
H. Xu and D. Zhang, Smooth sample average approximation of stationary points in nonsmooth stochastic optimization and applications, Mathematical Programming, 119 (2009), 371401. doi: 10.1007/s1010700802140. 
[35] 
N. Yamashita, K. Taji and M. Fukushima, Unconstrained optimization reformulations of variational inequality problems, Journal of Optimization Theory and Applications, 92 (1997), 439456. doi: 10.1023/A:1022660704427. 
[36] 
C. Zhang and X. Chen, Stochastic nonlinear complementarity problem and applications to traffic equilibrium under uncertainty, Journal of Optimization Theory and Applications, 137 (2008), 277295. doi: 10.1007/s1095700893586. 
[37] 
C. Zhang, X. Chen and A. Sumalee, Robust Wardrops user equilibrium assignment under stochastic demand and supply: expected residual minimization approach, Transportation Research Part B, 2010 (Online first). 
[38] 
G. L. Zhou and L. Caccetta, Feasible semismooth Newton method for a class of stochastic linear complementarity problems, Journal of Optimization Theory and Applications, 139 (2008), 379392. doi: 10.1007/s1095700894062. 
[1] 
Suxiang He, Pan Zhang, Xiao Hu, Rong Hu. A sample average approximation method based on a Dgap function for stochastic variational inequality problems. Journal of Industrial and Management Optimization, 2014, 10 (3) : 977987. doi: 10.3934/jimo.2014.10.977 
[2] 
Liping Zhang, SoonYi Wu, ShuCherng Fang. Convergence and error bound of a Dgap function based Newtontype algorithm for equilibrium problems. Journal of Industrial and Management Optimization, 2010, 6 (2) : 333346. doi: 10.3934/jimo.2010.6.333 
[3] 
HuiQiang Ma, NanJing Huang. Neural network smoothing approximation method for stochastic variational inequality problems. Journal of Industrial and Management Optimization, 2015, 11 (2) : 645660. doi: 10.3934/jimo.2015.11.645 
[4] 
Lori Badea, Marius Cocou. Approximation results and subspace correction algorithms for implicit variational inequalities. Discrete and Continuous Dynamical Systems  S, 2013, 6 (6) : 15071524. doi: 10.3934/dcdss.2013.6.1507 
[5] 
Yusuke Murase, Atsushi Kadoya, Nobuyuki Kenmochi. Optimal control problems for quasivariational inequalities and its numerical approximation. Conference Publications, 2011, 2011 (Special) : 11011110. doi: 10.3934/proc.2011.2011.1101 
[6] 
Meng Xue, Yun Shi, Hailin Sun. Portfolio optimization with relaxation of stochastic second order dominance constraints via conditional value at risk. Journal of Industrial and Management Optimization, 2020, 16 (6) : 25812602. doi: 10.3934/jimo.2019071 
[7] 
Na Zhao, ZhengHai Huang. A nonmonotone smoothing Newton algorithm for solving box constrained variational inequalities with a $P_0$ function. Journal of Industrial and Management Optimization, 2011, 7 (2) : 467482. doi: 10.3934/jimo.2011.7.467 
[8] 
Z.Y. Wu, H.W.J. Lee, F.S. Bai, L.S. Zhang. Quadratic smoothing approximation to $l_1$ exact penalty function in global optimization. Journal of Industrial and Management Optimization, 2005, 1 (4) : 533547. doi: 10.3934/jimo.2005.1.533 
[9] 
H. N. Mhaskar, T. Poggio. Function approximation by deep networks. Communications on Pure and Applied Analysis, 2020, 19 (8) : 40854095. doi: 10.3934/cpaa.2020181 
[10] 
Zhiyan Ding, Qin Li. Constrained Ensemble Langevin Monte Carlo. Foundations of Data Science, 2022, 4 (1) : 3770. doi: 10.3934/fods.2021034 
[11] 
Mei Ju Luo, Yi Zeng Chen. Smoothing and sample average approximation methods for solving stochastic generalized Nash equilibrium problems. Journal of Industrial and Management Optimization, 2016, 12 (1) : 115. doi: 10.3934/jimo.2016.12.1 
[12] 
Bin Zhou, Hailin Sun. Twostage stochastic variational inequalities for CournotNash equilibrium with riskaverse players under uncertainty. Numerical Algebra, Control and Optimization, 2020, 10 (4) : 521535. doi: 10.3934/naco.2020049 
[13] 
Giacomo Dimarco. The moment guided Monte Carlo method for the Boltzmann equation. Kinetic and Related Models, 2013, 6 (2) : 291315. doi: 10.3934/krm.2013.6.291 
[14] 
Guillaume Bal, Ian Langmore, Youssef Marzouk. Bayesian inverse problems with Monte Carlo forward models. Inverse Problems and Imaging, 2013, 7 (1) : 81105. doi: 10.3934/ipi.2013.7.81 
[15] 
Ajay Jasra, Kody J. H. Law, Yaxian Xu. Markov chain simulation for multilevel Monte Carlo. Foundations of Data Science, 2021, 3 (1) : 2747. doi: 10.3934/fods.2021004 
[16] 
Theodore Papamarkou, Alexey Lindo, Eric B. Ford. Geometric adaptive Monte Carlo in random environment. Foundations of Data Science, 2021, 3 (2) : 201224. doi: 10.3934/fods.2021014 
[17] 
George Avalos, Thomas J. Clark. A mixed variational formulation for the wellposedness and numerical approximation of a PDE model arising in a 3D fluidstructure interaction. Evolution Equations and Control Theory, 2014, 3 (4) : 557578. doi: 10.3934/eect.2014.3.557 
[18] 
Vladimir Gaitsgory, Tanya Tarnopolskaya. Threshold value of the penalty parameter in the minimization of $L_1$penalized conditional valueatrisk. Journal of Industrial and Management Optimization, 2013, 9 (1) : 191204. doi: 10.3934/jimo.2013.9.191 
[19] 
Esther S. Daus, Shi Jin, Liu Liu. Spectral convergence of the stochastic galerkin approximation to the boltzmann equation with multiple scales and large random perturbation in the collision kernel. Kinetic and Related Models, 2019, 12 (4) : 909922. doi: 10.3934/krm.2019034 
[20] 
Burcu Özçam, Hao Cheng. A discretization based smoothing method for solving semiinfinite variational inequalities. Journal of Industrial and Management Optimization, 2005, 1 (2) : 219233. doi: 10.3934/jimo.2005.1.219 
Impact Factor:
Tools
Metrics
Other articles
by authors
[Back to Top]