1.
E. Anderson, H. Xu and D. Zhang
Varying
confidence levels for CVaR risk measures and minimax
limits.
Mathematical
Programming Series A.
2.
A.
Pichler and H. Xu
Quantitative
stability analysis for minimax distributionally
robust risk optimization.
Mathematical Programming Series B.
3. S. Guo and H. Xu
Distributionally robust shortfall risk optimization model and its approximation.
Mathematical Programming Series B, https://doi.org/10.1007/s10107-018-1307-z.
4. M. Battarra, B. Balcik and H. Xu
Disaster
preparedness using risk-assessment methods from earthquake engineering.
European
Journal of Operational Research. DOI: 10.1016/j.ejor.2018.02.014
5. X. Chen, H. Sun and H. Xu
Mathematical
Programming series A, https://link.springer.com/article/10.1007/s10107-018-1266-4.
6. Y. Liu, A. Pichler and H. Xu
Discrete Approximation and
Quantification in Distributionally Robust
Optimization.
Mathematics of Operations
Research, 2018.
7. Y. Liu, H. Xu, S. Yang and J.
Zhang
Distributionally Robust Equilibrium for Continuous Games:
Nash and Stackelberg Models.
European Journal of Operations Research, Vol. 265, pp. 631-643, 2018.
8. H. Xu, Y. Liu and S. Sun
Mathematical Programming Series A, http://link.springer.com/article/10.1007/s10107-017-1143-6,Vol.
169, pp. 489-529, 2018.
9. J. Zhang, H. Xu and L.W. Zhang
Quantitative Stability Analysis
of Stochastic Quasi-Variational Inequality Problems and Applications.
Mathematical Programming Series B, Vol. 165, pp: 433-470, 2017.
10. Y. Liu, R.
Meskarian and H. Xu
Distributionally
Robust Reward-Risk Ratio Optimization with Moments Constraints.
SIAM J. Optimization, Vol. 27, No. 2, pp. 957-985, 2017.
11. S. Guo, H. Xu and L. Zhang
Convergence Analysis for Mathematical Programs with Distributionally Robust Chance Constraint.
SIAM J. Optimization, Vol. 27, No. 2, pp. 784–816, 2017.
12. X. Tong, H. Xu, F. Wu, and Z. Zhao
Computational Management Science, 1-30. DOI: 10.1007/s10287-016-0251-8
13. J. Zhang, H. Xu and L.W. Zhang
Quantitative Stability Analysis for Distributionally Robust Optimization with Moment Constraints.
SIAM J. Optimization, Vol. 26, pp. 1855-1882, 2016.
14. S. Guo, H. Xu and L. Zhang
Optimization
Methods and Software,
2016.
15. A. Gourtani, H.
Xu, D. Pozo and T. Nguyen
Robust Unit Commitment with n-1
Security Criteria
Mathematics
Methods of Operations Research, 2016.
16. H. Sun and H. Xu
Convergence Analysis for Distributional
Robust Optimization and Equilibrium Problems
Mathematics of Operations Research, Vol. 41, pp. 377-401, 2015.
17. Y. Liu
and H. Xu
Entropic approximation
for mathematical programs with robust equilibrium constraints.
SIAM J.
Optimization, Vol. 24, pp. 933–958, 2014.
18. Yongchao Liu, Werner Roemisch
and Huifu Xu,
Quantitative Stability Analysis of Stochastic Generalized Equations.
SIAM J. Optimization. Vol. 24, pp. 467-497, 2014.
19. Hailin Sun, Huifu Xu, Rudabeh Meskarian and Yong Wang,
SIAM J. Optimization, Vol. 23, pp. 602-631, 2013.
20. H. Sun, H. Xu and Y. Wang,
A Smoothing Penalized Sample Average Approximation Method for Stochastic Programs with Second Order Stochastic Dominance Constraints
Asian Pacific Journal of Operations Research, Vol. 30, No. 3, June 2013
21. Arash Gourtani, David Pozo, Maria Teresa Vespucci
and Huifu Xu,
Medium-Term
Trading Strategy of a Dominant Electricity Producer.
Energy Systems. December 2013 http://link.springer.com/article/10.1007/s12667-013-0105-1
22. Y. Liu and H. Xu
Stability and Sensitivity
Analysis of Stochastic Programs with Second Order Dominance Constraints.
Mathematical Programming Series A, Vol. 142, pp. 435-460, 2013.
23. H. Xu and D. Zhang
Stochastic Nash equilibrium problems: sample average approximation and applications.
Computational Optimization and Applications, Vol. 55, pp. 597-645, 2013.
Journal of Optimization Theory and Applications. Vol. 161, pp. 257-284, 2014.
Convergence Analysis of Stationary Points in Sample Average Approximation of Stochastic Programs with Second Order Stochastic Dominance Constraints
Mathematical Programming Series A, Vol. 143, pp. 489-529, 2014.
Optimization, Vol. 62, pp. 1627-1650, 2013.
Stability Analysis of One Stage Stochastic Mathematical Programs with Complementarity Constraints
Journal of Optimization Theory and Applications, Vol. 152, pp. 573-555, 2012.
European
Journal of Operational Research, 2011.
Mathematics
of Operations Research, Vol.36, No. 4, pp.
670-694, 2011.
A note on uniform exponential convergence of sample average approximation of random functions,
Journal of Mathematical Analysis and Applications, Vol. 385, pp. 698-708, 2011.
Mathematics of Operations Research, Vol. 36, No. 3, pp. 568-592, 2011.
Stochastic multiobjective optimization: sample average approximation and applications.
Journal of Optimization Theory and Applications, Vol. 151, 2011.
SIAM Journal on Optimization,Vol. 21, No. 3, pp. 609-705, 2011.
Approximating Stationary Points of Stochastic Mathematical Programs with Variational Inequality Constraints via Sample Averaging.
http://www.springerlink.com/content/5622m6138q878826/fulltext.pdf
Set-Valued and Variational
Analysis, Vol. 19, pp. 283-309, 2011.
Monte Carlo Methods for Mean-Risk Optimization and Portfolio Selection.
Computational Management Sciences, 2010.
Journal of Mathematical Analysis and Applications, Vol.368, pp.692-710, 2010.
Necessary Optimality Conditions for two-stage Stochastic Programs with Equilibrium Constraints
SIAM J. Optimization, Vol. 20, pp.
1685-1715, 2010.
Sample average approximation methods for a class of stochastic variational inequality problems.
Asian Pacific Journal of Operations Research, Vol. 27, pp. 103-119, 2010 (Special issue edited by W. Sun, T. Tanino and H. Xu )
A two stage stochastic equilibrium model for electricity markets with two way contracts.
Mathematical Methods of
Operations Research, Vol. 71, pp. 1-45, 2010.
Single and multi-Period Optimal Inventory Control Models with Risk-Averse Constraints
European Journal of Operations Research,
Vol. 199, pp. 420–434, 2009.
A Stochastic Multiple Leader Stackelberg Model: Analysis, Computation, and Application
Operations Research, Vol. 57, No. 5, pp. 1220–1235 2009. (supplementary
material)
Approximating stationary points of stochastic optimization problems in Banach space.
Journal of Mathematical Analysis
and Applications, Vol.
347, pp. 333-343, 2008.
Stochastic Approximation Approaches
to the Stochastic Variational Inequality Problem.
IEEE Transactions on Automatic Control, Vol. 53, pp. 1462-1475, 2008.
Mathematical Programming, series A, Vol 119, 2009,
371-401.
Optimization, Vol. 57, pp. 395-418, 2008. (Optimization: free access to selected
2008 articles: http://www.tandf.co.uk/journals/pdf/freeaccess/gopt.pdf)
Mathematical Methods of Operations Research, Vol. 67, pp. 423-441, 2008.
Journal of Computational Mathematics,
Vol. 24, pp. 733-748, 2006.
Mathematics of Operations
Research, Vol. 32, No. 3, pp. 648-668, 2007.
Uniform Laws of Large Numbers for Set-Valued Mappings and Subdifferentials of Random Functions.
Journal of Mathematical Analysis
and Applications, Vol.325, pp. 1390-1399, 2007.
SIAM Journal on Optimization, Vol. 17, pp. 891-919, 2006.
SIAM
Journal on Optimization, Vol.16, PP. 670-696, 2006.
Modelling the effects of
interconnection between electricity markets.
Mathematical Methods of Operations Research, Vol. 65, pp.1-26,
2007.
Optimal supply functions in
electricity markets with option contracts and nonsmooth
costs.
Mathematical Methods of
Operations Research, Vol. 63, No.
3, pp. 387-411, 2006.
Epsilon-optimal bidding in electricity markets with discontinuous market distribution function.
SIAM Journal on Control and Optimization, Vol. 44,
pp.1391-1418, 2005.
An
MPCC approach for stochastic Stackelberg-Nash-Cournot Equilibrium,
Optimization, Vol. 54,
pp. 27-57, 2005.
Implicit smoothing and its application to optimization with piecewise smooth equality constraints.
Journal of Optimization Theory and Applications, Vol. 124, No. 3, 2005.
Contracts and supply functions in electricity.
Journal of Optimization Theory and Applications, Vol. 124, No. 2, pp. 257-283, 2005.
Nash equilibria in electricity markets,
Mathematical Methods of Operations Research, Vol. 60, pp. 215-238, 2004.
Point-based set-valued approximation, C-differentiable operator and application,
Optimization, Vol. 52, pp. 127-143, 2003.
Nash equilibria in electricity markets with fixed prices points,
Optimization and Industry: New Frontiers, Panos Pardalos and Victor Korotkich eds, Kluwer Academic Publishers, pp. 141-157, 2003.
Necessary and sufficient conditions for optimal offers in electricity markets,
SIAM Journal on Control and Optimization, Vol.
41, pp. 1212-1228, 2002.
Picard iteration for nonsmooth equations,
Journal of Computational Mathematics, Vol. 19, No. 6, pp. 583-590, 2001.
Adaptive smoothing method, deterministically computable generalized Jacobians and Newton's method.
Journal of Optimization Theory and Applications, Vol. 109, No. 1, pp. 215-224, 2001.
Regularized gap functions and D-gap functions for nonsmooth variational inequalities.
Optimization and Related Topics, A. Rubinov and B. Glover eds., Kluwer Academic Publishers, 2001. pdf
Level function of some optimal value
function
Optimization and Related Topics, A. Rubinov and B. Glover eds., Kluwer Academic Publishers, 2001. pdf
Level function method for quasi-convex programming
Journal of Optimization Theory and Applications, Vol. 108, No. 2, 2001.pdf
Continuous approximations to generalized Jacobians.
Optimization, Vol. 46, pp. 221--246, 1999. pdf
Approximations to the Clarke generalized
Jacobian and nonsmooth least-squares minimization
Progress in Optimization: Contribution from Australasia, E. Eberhard et al eds., Kluwer Academic Publishers, pp. 193--210, 1999. pdf
Set-valued approximation and Newton's methods
Mathematical Programming, Vol. 84, No. 2, 1999, pp. 401-420.pdf
Strict lower sub-differentiability and application.
Journal of the Australian Mathematical Society, Series B, Vol. 40, 1999,
pp. 379-391. pdf
Numerical methods for abstract convex programming,
Optimization Techniques and Applications (International Conference on Optimization Techniques and Applications), Curtin University,
L. Caccetta et al eds., Vol. 1, pp. 229-234, 1998
New version of Newton's method for nonsmooth equations.
Journal of Optimization Theory and Applications, Vol. 93, pp. 395-414, 1997.pdf
Approximate Newton methods for nonsmooth equations
Journal of Optimization Theory and Applications, Vol. 93, pp. 373-394, 1997.pdf
On the extension of minimization algorithms from convex to lower sub-differentiable problems
Proceedings of the Optimization Mini-conference III, B. M. Glover, B. D. Craven and D. Ralph eds., University of Melbourne, pp. 13-23, 1996.
Stochastic penalty function methods for nonsmooth constrained minimization.
Journal of Optimization Theory and Applications, Vol. 88, pp. 709-724, 1996.pdf
A sufficient condition for nonlinear
nonconvex L1-minimization.
Journal of Ningbo University, 1996.
Non-descent sub-gradient method for nonsmooth constrained minimization,
Numerical Mathematics, A Journal of Chinese Universities, English Series. Vol. 3, No 2. 1994. pdf
L1-penalty function method for nonsmooth equality and inequality constrained minimization.
Journal of Ningbo University, Vol. 7, No 2. 1994.
Some remarks on collinear scaling methods for unconstrained minimization.
Journal of Ningbo University, Vol. 7, No. 1, 1994.
Penalty function method for a class of nonsmooth nonlinear programming problems.
Journal of Ningbo University, Vol 5, No. 2, 1992.
L1-Exact penalty function method for non-differentiable constrained minimization
Journal of Ningbo University, Vol. 5, No. 1, 1992.
Broyden family
of collinear scaling algorithm for unconstrained optimization.
Numerical Mathematics, A Journal of Chinese Universities, Vol. 13, No. 4, 1991.
On the convergence of inexact Newton Method at singular points.
Journal of Ningbo University, Vol. 3, No.1, 1990.
Mathematical
Review of my papers
Reports
and Manuscripts
S. Guo, H. Xu and L. Zhang, Continuous Behavioural functions equilibria and approximation schemes in Bayesian games with non-finite type and action spaces, arXiv:1710.04968, 2017.
Under revision
E. Delage, S. Guo and H. Xu, Shortfall risk models when information of loss function is incomplete, Optimization online, April 2018.
Y. Chen,
H. Sun and H. Xu,
Decomposition
Methods for Solving Two-Stage Distributionally Robust
Optimization Problems, Optimization-online, 2018.
H.
Xu
Level
function method for abstract convex programming.
Manuscripts,
School of Information Technology and Mathematical Sciences, University of Ballarat, Australia, 1998 (unpublished).