Jay H. Lee

发表

A model predictive control approach for fab-wide scheduling in semiconductor manufacturing facilities

Hong Jang, Tae Yeong Jung, Kevin Yeh, 2013 .

An approximate dynamic programming based approach to dual adaptive control

Jong Min Lee, Jay H. Lee, Jay H. Lee, 2009 .

Optimal design of heat and water recovery system utilizing waste flue gases for refinery CO2 reduction

Jay H. Lee, Haeun Yoo, Kosan Roh, 2019, Comput. Chem. Eng..

Optimization of the various modes of flexible operation for post-combustion CO2 capture plant

Jay H. Lee, Muhammad Zaman, Jay H. Lee, 2015, Comput. Chem. Eng..

Robust inferential control of multi-rate sampled-data systems

Jay H. Lee, Manfred Morari, Jay H. Lee, 1992 .

Special issue in Honor of Manfred Morari's 60th Birthday

Richard D. Braatz, Jay H. Lee, 2014, Comput. Chem. Eng..

DISTURBANCE MODELING FOR PROCESS CONTROL VIA HIDDEN MARKOV MODELS

Jay H. Lee, Wee Chin Wong, 2007 .

Dynamic analysis and linear model predictive control for operational flexibility of post-combustion CO2 capture processes

Jay H. Lee, Seongmin Heo, Howoun Jung, 2020, Comput. Chem. Eng..

A set based approach to detection and isolation of faults in multivariable systems

Jay H. Lee, Parthasarathy Kesavan, Jay H. Lee, 2001 .

Simulation-based design of dual-mode controller for non-linear processes

Jong Min Lee, Jay H. Lee, Jay H. Lee, 2008 .

Input sequence design for parametric identification of nonlinear systems

Jay H. Lee, Y. Chikkula, J.H. Lee, 1997, Proceedings of the 1997 American Control Conference (Cat. No.97CH36041).

Extended Kalman Filter Based Nonlinear Model Predictive Control

Jay H. Lee, N. Lawrence Ricker, Jay H. Lee, 1993, 1993 American Control Conference.

Robust Dual Control of Batch Processes with Parametric Uncertainty using Proximal Policy Optimization

Jay H. Lee, Jay H. Lee, Ha-Eun Byun, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

Robust measurement selection

Manfred Morari, Jay H. Lee, Jay H. Lee, 1991, Autom..

Screening plant designs and control structures for uncertain systems

Richard D. Braatz, Jay H. Lee, Manfred Morari, 1996 .

Subspace identification for batch processes

Jay H. Lee, A. W. Dorsey, 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

Application of Wavelets in Process Control

Jay H. Lee, Yugender Chikkula, 1994 .

Constrained linear state estimation - a moving horizon approach

Jay H. Lee, James B. Rawlings, Christopher V. Rao, 2001, Autom..

A Survey on State Estimation of Nonlinear Systems

Hong Jang, Jay H. Lee, Su-Hang Choi, 2014 .

Optimal control of a fed-batch bioreactor using simulation-based approximate dynamic programming

Jay H. Lee, Niket S. Kaisare, Catalina Valencia Peroni, 2005, IEEE Transactions on Control Systems Technology.

Screening plant designs and control structures for uncertain systems

Richard D. Braatz, Jay H. Lee, Manfred Morari, 1994 .

Optimal processing pathway for the production of biodiesel from microalgal biomass: A superstructure based approach

Jay H. Lee, Rafiqul Gani, Jay H. Lee, 2013, Comput. Chem. Eng..

An Extended Kalman Filter Formulation for Systematic Transfer of Information from Batch to Batch

Jay H. Lee, Andrew W. Dorsey, Stephen A. Russell, 2003 .

Integrated Identification and Robust Control

Jay H. Lee, Brian L. Cooley, 1997 .

Crude Selection Integrated with Optimal Refinery Operation by Combining Optimal Learning and Mathematical Programming

Jay H. Lee, Joohyun Shin, 2017 .

New performance indicators for adsorbent evaluation derived from a reduced order model of an idealized PSA process for CO2 capture

Hong Jang, Jay H. Lee, Jay H. Lee, 2017, Comput. Chem. Eng..

Dynamic analysis and Model predictive control for Operational flexibility of Post-combustion CO2 cpature process

Jay H. Lee, Howoun Jung, 2019 .

COMPLEX DECISION MAKING AT A RE-ENTRANT FLOW STATION UNDER UNCERTAINTY

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2007 .

Control-Relevant Experiment Design for Multivariable Systems

Jay H. Lee, 1997 .

Model-based monitoring and control of batch pulp digester

Jay H. Lee, A. K. Datta, S. Vanchinathan, 1994, Proceedings of 1994 American Control Conference - ACC '94.

Subspace identification based inferential control of a continuous pulp digester

Jay H. Lee, Raja Amirthalingam, 1997 .

Tuning of model predictive controllers for robust performance

Jay H. Lee, Z. H. Yu, Jay H. Lee, 1994 .

A generic framework for integrated quality and profile control for industrial batch processes

Jay H. Lee, Kwang S. Lee, Jay H. Lee, 2001 .

Multi-time scale procurement planning considering multiple suppliers and uncertainty in supply and demand

Jay H. Lee, Jay H. Lee, Joohyun Shin, 2016, Comput. Chem. Eng..

Development of batch proportional-integral-derivative controller

Jay H. Lee, Su Whan Sung, Jay H. Lee, 2018, Korean Journal of Chemical Engineering.

An introduction to a dynamic plant-wide optimization strategy for an integrated plant

Jay H. Lee, Jong Min Lee, Joseph Lu, 2004, Comput. Chem. Eng..

Simultaneous Design and Operation Decisions for Biorefmery Supply Chain Networks: Centralized vs. Distributed System

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2010 .

A Risk based Approach to Estimate Key Uncertainties

Jay H. Lee, Matthew J. Realff, Farminder S. Anand, 2010 .

Fault detection and classification using artificial neural networks

Jay H. Lee, Seongmin Heo, Jay H. Lee, 2018 .

Modified subspace identification for long-range prediction model for inferential control

Jay H. Lee, Yangdong Pan, Jay H. Lee, 2008 .

Integrated scheduling of vessel dispatching and port operations in the closed-loop shipping system for transporting petrochemicals

Jay H. Lee, Jay H. Lee, Heungjo An, 2019, Comput. Chem. Eng..

Deep reinforcement learning based finite-horizon optimal tracking control for nonlinear system

Byung Jun Park, Jong Min Lee, Jay H. Lee, 2018 .

ITERATIVE LEARNING CONTROL APPLIED TO BATCH PROCESSES: AN OVERVIEW

Jay H. Lee, Kwang S. Lee, Jay H. Lee, 2006 .

Parallel neural networks for improved nonlinear principal component analysis

Jay H. Lee, Seongmin Heo, Jay H. Lee, 2019, Comput. Chem. Eng..

Information Flow Based Decomposition of Decision-Making Problems Involving Partial Observability

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2008 .

Integrating operations and control: A perspective and roadmap for future research

Michael Baldea, Prodromos Daoutidis, Sigurd Skogestad, 2018, Comput. Chem. Eng..

Convergence of constrained model-based predictive control for batch processes

Jay H. Lee, Kwang S. Lee, Jay H. Lee, 2000, IEEE Trans. Autom. Control..

Optimal design for flexible operation of the post-combustion CO2 capture plant with uncertain economic factors

Hong Jang, Jay H. Lee, Jay H. Lee, 2016, Comput. Chem. Eng..

On interfacing model predictive controllers with a real-time optimizer

Jong Min Lee, Jay H. Lee, Joseph Z. Lu, 2003 .

Control structure selection: issues and a new methodology

Jay H. Lee, Manfred Morari, Jay H. Lee, 1990 .

Recursive data-based prediction and control of product quality for a PMMA batch process

Jay H. Lee, Yangdong Pan, Jay H. Lee, 2003 .

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2010 .

Nonlinear Dynamic Trend Modeling Using Feedback Neural Networks and Prediction Error Minimization

Jay H. Lee, Yangdong Pan, Su W. Sung, 2000 .

Deep Deterministic Policy Gradient Algorithm for Batch Process Control

Jay H. Lee, Haeun Yoo, Boeun Kim, 2019 .

Model-based predictive control combined with iterative learning for batch or repetitive processes

Jay H. Lee, Kwang Soon Lee, 1998 .

Analysis and comparison of single period single level and bilevel programming representations of a pre-existing timberlands supply chain with a new biorefinery facility

Kevin Yeh, Jay H. Lee, Matthew J. Realff, 2014, Comput. Chem. Eng..

On Interfacing Model Predictive Controllers with Low-level Loops

Sunwon Park, Jay H. Lee, Yongho Lee, 1999 .

Dynamic programming in a heuristically confined state space: a stochastic resource-constrained project scheduling application

Jay H. Lee, Matthew J. Realff, Jaein Choi, 2004, Comput. Chem. Eng..

Model predictive control technique combined with iterative learning for batch processes

Jay H. Lee, Kwang S. Lee, In‐Shik Chin, 1999 .

Reinforcement Learning - Overview of recent progress and implications for process control

Jay H. Lee, Jay H. Lee, Kuang-Hung Liu, 2019, Comput. Chem. Eng..

Simulation-based learning of cost-to-go for control of nonlinear processes

Jong Min Lee, Jay H. Lee, Jay H. Lee, 2004 .

Two‐step procedure for data‐based modeling for inferential control applications

Jay H. Lee, Su Whan Sung, Raja Amirthalingam, 2000 .

Simulation based approach for improving heuristics in stochastic resource-constrained project scheduling problem

Jay H. Lee, Matthew J. Realff, Jaein Choi, 2003 .

Hybrid cybernetic model-based simulation of continuous production of lignocellulosic ethanol: Rejecting abruptly changing feed conditions

Jay H. Lee, Doraiswami Ramkrishna, Wee Chin Wong, 2010 .

Real-time control of photoresist development process

Arthur Tay, Weng Khuen Ho, Jay H. Lee, 2005, SPIE Advanced Lithography.

Controlled exploration of state space in off-line ADP and its application to stochastic shortest path problems

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2009, Comput. Chem. Eng..

Machine learning: Overview of the recent progresses and implications for the process systems engineering field

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2017, Comput. Chem. Eng..

An on-line batch span minimization and quality control strategy for batch and semi-batch processes

Sunwon Park, Jay H. Lee, Kwang S. Lee, 2000 .

Control relevant identification of ill-conditioned systems: Estimation of gain directionalyty

Wei Li, Jay H. Lee, Jay H. Lee, 1996 .

Multi-timescale, multi-period decision-making model development by combining reinforcement learning and mathematical programming

Jay H. Lee, Jay H. Lee, Joohyun Shin, 2019, Comput. Chem. Eng..

Neuro-dynamic programming method for MPC 1

Jay H. Lee, Jong Min Lee, Jay H. Lee, 2001 .

Decision oriented Bayesian design of experiments

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2009 .

Min-max predictive control techniques for a linear state-space system with a bounded set of input matrices

Jay H. Lee, Brian L. Cooley, 2000, Autom..

Simulation-Based Dual Mode Controller for Nonlinear Processes

Jong Min Lee, Jay H. Lee, 2004 .

Iterative learning control-based batch process control technique for integrated control of end product properties and transient profiles of process variables

Jay H. Lee, Kwang S. Lee, Jay H. Lee, 2003 .

Particle size distribution control of a semi-batch reactor using model predictive control

Jay H. Lee, Kangwook Lee, Dae Ryook Yang, 2001 .

Realistic disturbance modeling using Hidden Markov Models: Applications in model-based process control

Jay H. Lee, Wee Chin Wong, Jay H. Lee, 2009 .

Special issue on process dynamics and control

Jay H. Lee, S. Joe Qin, En-Sup Yoon, 2003 .

An investigation into the hydrodynamics of a spinning cone column: CFD simulations by an Eulerian-Lagrangian approach

Jay H. Lee, Jay H. Lee, Seongwoong Bae, 2020, Comput. Chem. Eng..

MILP based value backups in partially observed Markov decision processes (POMDPs) with very large or continuous action and observation spaces

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2013, Comput. Chem. Eng..

An algorithmic framework for improving heuristic solutions: Part I. A deterministic discount coupon traveling salesman problem

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2004, Comput. Chem. Eng..

Worst-case formulations of model predictive control for systems with bounded parameters

Zhenghong Yu, Jay H. Lee, Jay H. Lee, 1997, Autom..

Target identification in biological systems using network connectivity information from literature mining databases

Jay H. Lee, Dmitriy Leyfer, Ugur Guner, 2010 .

Deep Reinforcement Learning Based Finite-Horizon Optimal Control for a Discrete-Time Affine Nonlinear System

Byung Jun Park, Jong Min Lee, Jay H. Lee, 2018, 2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

A methodology for the sustainable design and implementation strategy of CO2 utilization processes

Rebecca Frauzem, Jay H. Lee, Rafiqul Gani, 2016, Comput. Chem. Eng..

Identifying the interacting positions of a protein using Boolean learning and support vector machines

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2006, Comput. Biol. Chem..

State-space interpretation of model predictive control

Manfred Morari, Jay H. Lee, Carlos E. Garcia, 1994, Autom..

Optimization of a Fed-Batch Bioreactor Using Simulation-Based Approach

Jay H. Lee, Catalina Valencia Peroni, Niket S. Kaisare, 2004 .

Approximate dynamic programming-based approaches for input-output data-driven control of nonlinear processes

Jay H. Lee, Jong Min Lee, Jay H. Lee, 2005, Autom..

Improved Parameter Estimation of Ill-Conditioned Problems

Jay H. Lee, Boeun Kim, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth

Jay H. Lee, Sang Lee, Tae Kim, 2012, BMC Systems Biology.

An algorithmic framework for improving heuristic solutions: Part II. A new version of the stochastic traveling salesman problem

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2004, Comput. Chem. Eng..

Integrated Identification and Robust Control

Jay H. Lee, Brian L. Cooley, B. L. Cooley, 1997 .

Partial least squares (PLS) based monitoring and control of batch digesters

Jay H. Lee, Parthasarathy Kesavan, Victor Saucedo, 2000 .

Sustainability analysis of CO2 capture and utilization processes using a computer-aided tool

Jay H. Lee, Haeun Yoo, Kosan Roh, 2018, Journal of CO2 Utilization.

From robust model predictive control to stochastic optimal control and approximate dynamic programming: A perspective gained from a personal journey

Jay H. Lee, Jay H. Lee, 2014, Comput. Chem. Eng..

Use of two-stage optimization in model predictive control of stable and integrating systems

Jay H. Lee, Jian Xiao, 2000 .

General Adsorbent Library and Evaluation (GALE) Software Tool for CO2 Capture

Jay H. Lee, Seongbin Ga, Jihan Kim, 2019 .

Model predictive control: Review of the three decades of development

Jay H. Lee, Jay H. Lee, 2011 .

Energy supply planning and supply chain optimization under uncertainty

Jay H. Lee, Jay H. Lee, 2014 .

Building inferential prediction models of batch processes using subspace identification

Jay H. Lee, Andrew W. Dorsey, 2003 .

An On-line Batch Span Minimization and Quality Control Strategy for Batch and Semi-Batch Processes

Sunwon Park, Jay H. Lee, Kwang S. Lee, 2000 .

Data-based construction of feedback-corrected nonlinear prediction model using feedback neural networks

Jay H. Lee, Yangdong Pan, Su W. Sung, 2001 .

Approximate Dynamic Programming Strategies and Their Applicability for Process Control: A Review and Future Directions

Jong Min Lee, Jay H. Lee, Jay H. Lee, 2004 .

A numerical projection-based approach to nonlinear model reduction and identification

Jay H. Lee, Su Whan Sung, Yangdong Pan, 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

Dual Adaptive Control of a Fed-Batch Bioreactor Based on Approximate Dynamic Programming

Jay H. Lee, Boeun Kim, Ha-Eun Byun, 2019 .

Model predictive control: past, present and future

Jay H. Lee, Manfred Morari, Jay H. Lee, 1999 .

Optimal Harvest Management Adaptation for a New Biorefinery Investment in a Timberlands Supply Chain Using a Modified Cyclic Scheduling Model

Kevin Yeh, Jay H. Lee, Matthew J. Realff, 2015 .

Recursive data-based prediction and control of product quality for a batch PMMA reactor

Jay H. Lee, Yangdong Pan, Jay H. Lee, 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

Period-robust repetitive model predictive control

Jay H. Lee, Manish Gupta, Jay H. Lee, 2006 .

Processing History Dependent Control Parameter Estimation in Multi-step Batch Processes

Hana Lee, Jay H. Lee, Joohyun Shin, 2013 .

Fast moving horizon estimation for a two-dimensional distributed parameter system

Richard D. Braatz, Hong Jang, Jay H. Lee, 2014, Comput. Chem. Eng..

Modified Subspace Identification Method for Building a Long-Range Prediction Model for Inferential Control

Jay H. Lee, Yangdong Pan, 2003 .

Two stage stochastic bilevel programming model of a pre-established timberlands supply chain with biorefinery investment interests

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2015, Comput. Chem. Eng..

Superstructure optimization of biodiesel production from microalgal biomass

Jay H. Lee, Rafiqul Gani, Jay H. Lee, 2013 .

Operational planning and optimal sizing of microgrid considering multi-scale wind uncertainty

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2017 .

A model-based predictive control approach to repetitive control of continuous processes with periodic operations

Jay H. Lee, Kwang S. Lee, Seshatre Natarajan, 2001 .

A Q‐Learning‐based method applied to stochastic resource constrained project scheduling with new project arrivals

Jay H. Lee, Matthew J. Realff, Jaein Choi, 2007 .

Subspace identification based inferential control applied to a continuous pulp digester

Jay H. Lee, Raja Amirthalingam, Jay H. Lee, 1999 .

Optimal processing pathway selection for microalgae-based biorefinery under uncertainty

Jay H. Lee, Rafiqul Gani, Muhammad Zaman, 2015, Comput. Chem. Eng..

State estimation based model predictive control applied to shell control problem: a case study

Jay H. Lee, Manfred Morari, Wei Li, 1994 .

Control-relevant experiment design for multivariable systems described by expansions in orthonormal bases

Jay H. Lee, Brian L. Cooley, B. L. Cooley, 2001, Autom..

An optimization based strategy for crude selection in a refinery with lube hydro-processing

Jay H. Lee, Jay H. Lee, Joohyun Shin, 2017, Comput. Chem. Eng..

A real time adaptive dynamic programming approach for planning and scheduling

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2006 .

A Real Time Approximate Dynamic Programming Approach: A High Dimensional Supply Chain Application

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2011 .

Sparse identification in chemical master equations for monomolecular reaction networks

Richard D. Braatz, Hong Jang, Jay H. Lee, 2014, 2014 American Control Conference.

Stochastic optimization with value function approximation for micro-grid operation

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

PLS Based Monitoring and Control of Batch Digesters

Jay H. Lee, Parthasarathy Kesavan, Gopal A. Krishnagopalan, 1998 .

Optimal decision-oriented Bayesian design of experiments

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2010 .

Modeling and Identification for NonlinearModel Predictive Control: Requirements,Current Status and Future Research Needs

Jay H. Lee, 2000 .

Robust dual adaptive control of semi-batch process based on approximate dynamic programming

Jay H. Lee, Boeun Kim, Ha Eun Byun, 2019 .

Regularized maximum likelihood estimation of sparse stochastic monomolecular biochemical reaction networks

Richard D. Braatz, Hong Jang, Jay H. Lee, 2016, Comput. Chem. Eng..

A Unified Framework for Combined Quality and Tracking Control of Batch Processes

Jay H. Lee, Kwang S. Lee, S. Chin, 1999 .

Integrated State Estimation, Fault Detection and Diagnosis for Nonlinear Systems

Jay H. Lee, Douglas Robertson, 1993, 1993 American Control Conference.

Repetitive model predictive control applied to a simulated moving bed chromatography system

Jay H. Lee, Seshatre Natarajan, Jay H. Lee, 2000 .

Optimal Learning Control Combined with Quality Inferential Control for Batch and Semi-batch Processes

Jay H. Lee, Jinhoon Choi, Kwang Soon Lee, 1999 .

Move blocking strategy applied to re-entrant manufacturing line scheduling

Hong Jang, Jay H. Lee, Jay H. Lee, 2015 .

Model-based iterative learning control with a quadratic criterion for time-varying linear systems

Jay H. Lee, Kwang S. Lee, Won C. Kim, 2000, Autom..

Optimal design of microalgae-based biorefinery: Economics, opportunities and challenges

Jay H. Lee, Rafiqul Gani, Jay H. Lee, 2015 .

Inferential product quality control of a multistage batch plant

Jay H. Lee, Andrew W. Dorsey, Stephen A. Russell, 2004 .

Issues in the Application of Nonlinear Estimation for Improving Product Quality Control in Batch and Semi-Batch Processes

Jay H. Lee, Douglas G. Robertson, Stephen A. Russell, 1996 .

Synthesis of Optimal Processing Pathway for Microalgae-based Biorefinery under Uncertainty

Jay H. Lee, Rafiqul Gani, Muhammad Rizwan, 2015 .

A Hidden Markov disturbance model for Offset-free linear model predictive control

Jay H. Lee, Wee Chin Wong, Jay H. Lee, 2008 .

Robust Control Structure Selection

Richard D. Braatz, Jay H. Lee, Manfred Morari, 1993 .

Analysis and optimization of multi-path CCU system using a computer-aided tool

Jay H. Lee, Hasan Imran, Wonseok Chung, 2019 .

Screening tools for robust control structure selection

Richard D. Braatz, Manfred Morari, Jay H. Lee, 1995, Autom..

Procurement Planning of Refinery Integrated with Production System by Quantifying the Effect of the Gap Between Supply and Demand on the Production System’s Performance

Jay H. Lee, Joohyun Shin, Yechan Choi, 2018 .

Approximate dynamic programming based approach to process control and scheduling

Jay H. Lee, Jong Min Lee, Jay H. Lee, 2006, Comput. Chem. Eng..

Control structure selection and robust control system design for a high-purity distillation column

Manfred Morari, Jay H. Lee, Parthasarathy Kesavan, 1997, IEEE Trans. Control. Syst. Technol..

Integrated quality and tracking control of a batch PMMA reactor using a QBMPC technique

Jay H. Lee, Hyun-Ku Rhee, Kwang S. Lee, 2000 .

Multi-phase particle-in-cell coupled with population balance equation (MP-PIC-PBE) method for multiscale computational fluid dynamics simulation

Richard D. Braatz, Jay H. Lee, Jay H. Lee, 2020, Comput. Chem. Eng..

A method for the estimation of infrequent abrupt changes in nonlinear systems

Jay H. Lee, Douglas G. Robertson, Jay H. Lee, 1998, Autom..

A model-based deep reinforcement learning method applied to finite-horizon optimal control of nonlinear control-affine system

Byung Jun Park, Jong Min Lee, Jay H. Lee, 2020 .

Approximate dynamic programming: Application to process supply chain management

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2006 .

ACCOUNTING RISK IN MULTISTAGE STOCHASTIC PROBLEMS USING APPROXIMATE DYNAMIC PROGRAMMING

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2007 .

A model-based optimization of microalgal cultivation strategies for lipid production under photoautotrophic condition

Jay H. Lee, Jay H. Lee, Boeun Kim, 2019, Comput. Chem. Eng..

3. A Real Time Approximate Dynamic Programming Approach: A High Dimensional Supply Chain Application

Jay H. Lee, Matthew J. Realff, Nikolaos E. Pratikakis, 2011 .

On the use of constraints in least squares estimation and control

Jay H. Lee, Douglas G. Robertson, Jay H. Lee, 2002, Autom..

Optimal design and global sensitivity analysis of biomass supply chain networks for biofuels under uncertainty

Jay H. Lee, Matthew J. Realff, Jay H. Lee, 2011, Comput. Chem. Eng..