Guanghui (George) Lan Assistant Professor

• C. D. Dang and G. Lan, “On the Convergence Properties of Non-Euclidean Extragradient Methods for Variational Inequalities with  Generalized Monotone Operators“, submitted for publication, 2012. (Source Code and Instances.)
• G. Lan, “Level methods uniformly optimal for composite and structured nonsmooth convex optimization“, submitted for publication, 2011.
• G. Lan, “Bundle-type methods uniformly optimal for smooth and nonsmooth convex optimization“, submitted for publication, 2010.
• G. Lan and S. Ghadimi, “Optimal stochastic approximation algorithms for strongly convex stochastic
  composite optimization, Part II: shrinking procedures and optimal algorithms“, SIAM Journal on Optimization (under revision), 2010
• G. Lan and S. Ghadimi, “Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization, Part I: a generic algorithmic framework“, SIAM Journal on Optimization (under revision), 2010.
• G. Lan and R.D.C. Monteiro,  ”Iteration-complexity of first-order augmented Lagrangian methods for convex programming“, Mathematical Programming (under revision), 2009.
• G. Lan and R.D.C. Monteiro, “Iteration complexity of first-order penalty methods for convex programming“, Mathematical Programming (under revision), 2008.
• G. Lan, “An optimal method for stochastic composite optimization“, Mathematical Programming, 133 (1), 2012, 365-397.
• G. Lan, A. Nemirovski, and A. Shapiro, “Validation analysis of mirror descent stochastic approximation method“, Mathematical Programming, 2010. Forthcoming, Online first, DOI: 10.1007/s10107-011-0442-6.
• G. Lan, Z. Lu and R.D.C. Monteiro, “Primal-dual first-order methods with ${\cal O}(1/\epsilon)$ iterationcomplexity for cone programming“,  Mathematical Programming, 126 (2011), 1-29.
• A. Nemirovski, A.Juditsky, G. Lan, and A. Shapiro, “Robust stochastic approximation approach to stochasticprogramming“, SIAM Journal on Optimization 19 (2009), 1574-1609.
• G. Lan, R.D.C. Monteiro and T. Tsuchiya,  ”A polynomial predictor-corrector trust-region algorithm forlinear programming“, SIAM Journal on Optimization 19 (2009) 1918-1946.
• G. Lan, G. W. DePuy, and G. E. Whitehouse, “An effective and simple heuristic for the set covering problem“, European Journal of Operational Research 176 (2007), 1387-1403.
• G. Lan and G. W. DePuy, “On the effectiveness of incorporating randomness and memory into a multi-startmetaheuristic with application to the Set Covering Problem “, Computer & Industrial Engineering 51 (2006), 362-374

Publications before 2003 (in Chinese)

• X. Liu, X.,L.Ju, and G. Lan,  “Alternative process planning systems based on the feature, resource and knowledge models“, Computer Aided Engineering 12 (2003), 7-11.
• G. Lan, G. and L. Wang, “The decision-making strategies for integrating alternative processes planning withproduction scheduling“, Modern Manufacturing Engineering, 10 (2001), 24-26.
• G. Lan, R. Qian, and T. Li, “The technology and implementation of transmitting video data over Internet“, Research on Computer Application, 18 (2000), 33-37.

• G. Lan, “Efficient methods for stochastic composite optimization“, June 2008. This paper won INFORMS ICS student paper competition and George Nicholson Prize Competition second place in 2008. A modified version of this paper was later submitted to Mathematical Programming.

• Ph.D. Disseration, “Convex Optimization Under Inexact First-order Information”, Georgia Institute of Technology, August 2009, under the supervision of Drs. Arkadi Nemirovksi, Renato D.C. Monteiro and Alex Shapiro.
• M.S. Thesis, “An effective and simple heuristic to solve large-scale set covering problems based on Meta-RaPS”, University of Louisville, August 2004, under the supervision of Dr. Gail W. DePuy.

• SCPTool: An effective method for solving the set-covering problem (download).
• PDFirst: A primal-dual first-order method for linear and semidefinite programming (download).
• Stochapp: Stochastic approximation method for stochastic programming problems (download).