Indifference zone selection procedures: an indifference-zone selection procedure with minimum switching and sequential sampling. - L. Jeff Hong; Barry L. Nelson (WSC, 2003)

Discrete optimization via simulation using coordinate search. - L. Jeff Hong (WSC, 2005)

A sequential procedure for neighborhood selection-of-the-best in optimization via simulation. - Juta Pichitlamken; Barry L. Nelson; L. Jeff Hong (Eur. J. Oper. Res., 2006)

Discrete Optimization via Simulation Using COMPASS. - L. Jeff Hong; Barry L. Nelson (Oper. Res., 2006)

Stochastic trust region gradient-free method (strong): a new response-surface-based algorithm in simulation optimization. - Kuo-Hao Chang; L. Jeff Hong; Hong Wan (WSC, 2007)

Monte Carlo simulation in financial engineering. - Nan Chen; L. Jeff Hong (WSC, 2007)

Kernel estimation for quantile sensitivities. - Guangwu Liu; L. Jeff Hong (WSC, 2007)

A framework for locally convergent random-search algorithms for discrete optimization via simulation. - L. Jeff Hong; Barry L. Nelson (ACM Trans. Model. Comput. Simul., 2007)

09181 Working Group on Hybridization between R&S, DoE and Optimization. - Chun-Hung Chen; Liu Hong 001; Paul B. Kantor; David P. Morton; Juta Pichitlamken; Matthias W. Seeger (Sampling-based Optimization in the Presence of Uncertainty, 2009)

A Brief Introduction to Optimization via Simulation. - L. Jeff Hong; Barry L. Nelson (WSC, 2009)

Estimating the Mean of a Non-linear Function of Conditional Expectation. - Sandeep Juneja 001; L. Jeff Hong (WSC, 2009)

A General Framework of Importance Sampling for Value-at-risk and Conditional Value-at-risk. - Lihua Sun; L. Jeff Hong (WSC, 2009)

Estimating Quantile Sensitivities. - L. Jeff Hong (Oper. Res., 2009)

Conditional Monte Carlo Estimation of Quantile Sensitivities. - Michael C. Fu 001; L. Jeff Hong; Jian-Qiang Hu (Manag. Sci., 2009)

Simulating Sensitivities of Conditional Value at Risk. - L. Jeff Hong; Guangwu Liu (Manag. Sci., 2009)

Revisit of stochastic mesh method for pricing American options. - Guangwu Liu; L. Jeff Hong (Oper. Res. Lett., 2009)

Robust simulation of environmental policies using the DICE model. - Zhaolin Hu; Jing Cao; L. Jeff Hong (WSC, 2010)

Pathwise Estimation of Probability Sensitivities Through Terminating or Steady-State Simulations. - L. Jeff Hong; Guangwu Liu (Oper. Res., 2010)

Speeding up COMPASS for high-dimensional discrete optimization via simulation. - L. Jeff Hong; Barry L. Nelson; Jie Xu 004 (Oper. Res. Lett., 2010)

Asymptotic representations for importance-sampling estimators of value-at-risk and conditional value-at-risk. - Lihua Sun; L. Jeff Hong (Oper. Res. Lett., 2010)

Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation. - Jie Xu 004; Barry L. Nelson; L. Jeff Hong (ACM Trans. Model. Comput. Simul., 2010)

Monte Carlo estimation of value-at-risk, conditional value-at-risk and their sensitivities. - L. Jeff Hong; Guangwu Liu (WSC, 2011)

Large-scale ranking and selection using cloud computing. - Jun Luo; L. Jeff Hong (WSC, 2011)

Optimization via simulation using Gaussian process-based search. - Lihua Sun; L. Jeff Hong; Zhaolin Hu (WSC, 2011)

Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach. - L. Jeff Hong; Yi Yang; Liwei Zhang (Oper. Res., 2011)

Kernel Estimation of the Greeks for Options with Discontinuous Payoffs. - Guangwu Liu; L. Jeff Hong (Oper. Res., 2011)

Foreword. - L. Jeff Hong; Xiangtong Qi; Fugee Tsung (Ann. Oper. Res., 2012)

Fighting strategies in a market with counterfeits. - Jie Zhang; L. Jeff Hong; Rachel Q. Zhang (Ann. Oper. Res., 2012)

Robust Simulation of Global Warming Policies Using the DICE Model. - Zhaolin Hu; Jing Cao; L. Jeff Hong (Manag. Sci., 2012)

Robust selection of the best. - Weiwei Fan; L. Jeff Hong; Xiaowei Zhang 004 (WSC, 2013)

Linking statistical estimation and decision making through simulation. - Jin Fang; L. Jeff Hong (WSC, 2013)

Stochastic Trust-Region Response-Surface Method (STRONG) - A New Response-Surface Framework for Simulation Optimization. - Kuo-Hao Chang; L. Jeff Hong; Hong Wan (INFORMS J. Comput., 2013)

An Adaptive Hyperbox Algorithm for High-Dimensional Discrete Optimization via Simulation Problems. - Jie Xu 004; Barry L. Nelson; L. Jeff Hong (INFORMS J. Comput., 2013)

A frequentist selection-of-the-best procedure without indifference zone. - Weiwei Fan; L. Jeff Hong (WSC, 2014)

Scaling and modeling of call center arrivals. - Xiaowei Zhang 004; L. Jeff Hong; Jiheng Zhang (WSC, 2014)

Conditional Value-at-Risk Approximation to Value-at-Risk Constrained Programs: A Remedy via Monte Carlo. - L. Jeff Hong; Zhaolin Hu; Liwei Zhang (INFORMS J. Comput., 2014)

Estimating Sensitivities of Portfolio Credit Risk Using Monte Carlo. - L. Jeff Hong; Sandeep Juneja 001; Jun Luo (INFORMS J. Comput., 2014)

Balancing Exploitation and Exploration in Discrete Optimization via Simulation Through a Gaussian Process-Based Search. - Lihua Sun; L. Jeff Hong; Zhaolin Hu (Oper. Res., 2014)

Guest Editors' Introduction to Special Issue on the 2012 NSF workshop. - L. Jeff Hong; Jian-Qiang Hu; Seong-Hee Kim (ACM Trans. Model. Comput. Simul., 2014)

Monte Carlo Methods for Value-at-Risk and Conditional Value-at-Risk: A Review. - L. Jeff Hong; Zhaolin Hu; Guangwu Liu (ACM Trans. Model. Comput. Simul., 2014)

A statistical perspective on linear programs with uncertain parameters. - L. Jeff Hong; Henry Lam (WSC, 2015)

Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences. - Zhaolin Hu; L. Jeff Hong (WSC, 2015)

Input uncertainty and indifference-zone ranking & selection. - Eunhye Song; Barry L. Nelson; L. Jeff Hong (WSC, 2015)

Capacity reservation for time-sensitive service providers: An application in seaport management. - L. Jeff Hong; Xiaowei Xu 002; Sheng Hao Zhang (Eur. J. Oper. Res., 2015)

Chance Constrained Selection of the Best. - L. Jeff Hong; Jun Luo; Barry L. Nelson (INFORMS J. Comput., 2015)

Fully Sequential Procedures for Large-Scale Ranking-and-Selection Problems in Parallel Computing Environments. - Jun Luo; L. Jeff Hong; Barry L. Nelson; Yang Wu (Oper. Res., 2015)

Approximating data-driven joint chance-constrained programs via uncertainty set construction. - L. Jeff Hong; Zhiyuan Huang; Henry Lam (WSC, 2016)

Speeding up pairwise comparisons for large scale ranking and selection. - L. Jeff Hong; Jun Luo; Ying Zhong (WSC, 2016)

A simulation analytics approach to dynamic risk monitoring. - Guangxin Jiang; L. Jeff Hong; Barry L. Nelson (WSC, 2016)

Indifference-Zone-Free Selection of the Best. - Weiwei Fan; L. Jeff Hong; Barry L. Nelson (Oper. Res., 2016)

Ranking and selection with covariates. - Haihui Shen; L. Jeff Hong; Xiaowei Zhang 004 (WSC, 2017)

A new framework of designing sequential ranking-and-selection procedures. - Ying Zhong; L. Jeff Hong (WSC, 2017)

Kernel Smoothing for Nested Estimation with Application to Portfolio Risk Measurement. - L. Jeff Hong; Sandeep Juneja 001; Guangwu Liu (Oper. Res., 2017)

Gaussian Mixture Model-based Random Search for continuous Optimization via simulation. - Wenjie Sun; Zhaolin Hu; L. Jeff Hong (WSC, 2018)

Fully Sequential Ranking and Selection Procedures with PAC Guarantee. - Ying Zhong; L. Jeff Hong (WSC, 2018)

Replicated Computations Results (RCR) Report for "Reusing Search Data in Ranking and Selection: What Could Possibly Go Wrong?". - Xianyu Kuang; L. Jeff Hong (ACM Trans. Model. Comput. Simul., 2018)

Estimating Sensitivity to Input Model Variance. - Wendy Xi Jiang; Barry L. Nelson; L. Jeff Hong (WSC, 2019)

Offline Simulation Online Application: A New Framework of Simulation-Based Decision Making. - L. Jeff Hong; Guangxin Jiang (Asia Pac. J. Oper. Res., 2019)

Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Adversarial Defensiveness. - Li Xiao 005; Yijie Peng; L. Jeff Hong; Zewu Ke (CoRR, 2019)

A Dimension-free Algorithm for Contextual Continuum-armed Bandits. - Wenhao Li; Ningyuan Chen; L. Jeff Hong (CoRR, 2019)

A Novel Learning Framework for Sampling-Based Motion Planning in Autonomous Driving. - Yifan Zhang; Jinghuai Zhang; Jindi Zhang; Jianping Wang 001; Kejie Lu; L. Jeff Hong (AAAI, 2020)

Training Artificial Neural Networks by Generalized Likelihood Ratio Method: An Effective Way to Improve Robustness. - Li Xiao 005; Yijie Peng; L. Jeff Hong; Zewu Ke; Shuhuai Yang (CASE, 2020)

Online Risk Monitoring Using Offline Simulation. - Guangxin Jiang; L. Jeff Hong; Barry L. Nelson (INFORMS J. Comput., 2020)

Distributionally Robust Selection of the Best. - Weiwei Fan; L. Jeff Hong; Xiaowei Zhang 004 (Manag. Sci., 2020)

Option Pricing by Neural Stochastic Differential Equations: A Simulation-Optimization Approach. - Shoudao Wang; L. Jeff Hong (WSC, 2021)

Ranking and Selection with Covariates for Personalized Decision Making. - Haihui Shen; L. Jeff Hong; Xiaowei Zhang 004 (INFORMS J. Comput., 2021)

Learning-Based Robust Optimization: Procedures and Statistical Guarantees. - L. Jeff Hong; Zhiyuan Huang; Henry Lam (Manag. Sci., 2021)

Non-Myopic Knowledge Gradient Policy for Ranking and Selection. - Kexin Qin; L. Jeff Hong; Weiwei Fan (WSC, 2022)

Large-Scale Inventory Optimization: A Recurrent-Neural-Networks-Inspired Simulation Approach. - Tan Wan; L. Jeff Hong (CoRR, 2022)

Meaningful sensitivities: A new family of simulation sensitivity measures. - Xi Jiang 003; Barry L. Nelson; L. Jeff Hong (IISE Trans., 2022)

Solving Large-Scale Fixed-Budget Ranking and Selection Problems. - L. Jeff Hong; Guangxin Jiang; Ying Zhong (INFORMS J. Comput., 2022)

Robust Simulation with Likelihood-Ratio Constrained Input Uncertainty. - Zhaolin Hu; L. Jeff Hong (INFORMS J. Comput., 2022)

A New Likelihood Ratio Method for Training Artificial Neural Networks. - Yijie Peng; Li Xiao 005; Bernd Heidergott; L. Jeff Hong; Henry Lam (INFORMS J. Comput., 2022)

Speeding Up Paulson's Procedure for Large-Scale Problems Using Parallel Computing. - Ying Zhong; Shaoxuan Liu; Jun Luo; L. Jeff Hong (INFORMS J. Comput., 2022)

Knockout-Tournament Procedures for Large-Scale Ranking and Selection in Parallel Computing Environments. - Ying Zhong; L. Jeff Hong (Oper. Res., 2022)

Integrating Algorithmic Sampling-Based Motion Planning with Learning in Autonomous Driving. - Yifan Zhang; Jinghuai Zhang; Jindi Zhang; Jianping Wang 001; Kejie Lu; L. Jeff Hong (ACM Trans. Intell. Syst. Technol., 2022)

Sensitivity Analysis of CoVaR. - Han Fu; L. Jeff Hong; Guangxin Jiang (CASE, 2023)

Upper-Confidence-Bound Procedure for Robust Selection of The Best. - Yuchen Wan; L. Jeff Hong; Weiwei Fan (WSC, 2023)

Fast Approximation to Discrete-Event Simulation of Markovian Queueing Networks. - Tan Wang; Yingda Song; L. Jeff Hong (WSC, 2023)

Learning to Simulate: Generative Metamodeling via Quantile Regression. - L. Jeff Hong; Yanxi Hou; Qingkai Zhang; Xiaowei Zhang 004 (CoRR, 2023)

Large-Scale Inventory Optimization: A Recurrent Neural Networks-Inspired Simulation Approach. - Tan Wang; L. Jeff Hong (INFORMS J. Comput., 2023)

Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection. - Wenhao Li; Ningyuan Chen; L. Jeff Hong (J. Mach. Learn. Res., 2023)

Who Is Next: Patient Prioritization Under Emergency Department Blocking. - Wenhao Li; Zhankun Sun; L. Jeff Hong (Oper. Res., 2023)

Reliable Online Decision Making with Covariates. - Heng Luo; Zhiyang Liang 001; L. Jeff Hong (WSC, 2024)

AlphaRank: An Artificial Intelligence Approach for Ranking and Selection Problems. - Ruihan Zhou; L. Jeff Hong; Yijie Peng (CoRR, 2024)

Fast Discrete-Event Simulation of Markovian Queueing Networks through Euler Approximation. - L. Jeff Hong; Yingda Song; Tan Wang (CoRR, 2024)

Sample-Optimal Large-Scale Optimal Subset Selection. - Zaile Li; Weiwei Fan; L. Jeff Hong (CoRR, 2024)

Real-Time Derivative Pricing and Hedging with Consistent Metamodels. - Guangxin Jiang; L. Jeff Hong; Haihui Shen (INFORMS J. Comput., 2024)

Monte Carlo Estimation of CoVaR. - Weihuan Huang; Nifei Lin; L. Jeff Hong (Oper. Res., 2024)

Gaussian Process-Based Random Search for Continuous Optimization via Simulation. - Xiuxian Wang; L. Jeff Hong; Zhibin Jiang; Haihui Shen (Oper. Res., 2025)

The (Surprising) Sample Optimality of Greedy Procedures for Large-Scale Ranking and Selection. - Zaile Li; Weiwei Fan; L. Jeff Hong (Manag. Sci., 2025)

LLMs for Supply Chain Management. - Haojie Wang; Jiuyun Jiang; L. Jeff Hong; Guangxin Jiang (CoRR, 2025)

Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance. - Qingkai Zhang; L. Jeff Hong; Houmin Yan (CoRR, 2025)