Publications

Group highlights

(For a full list see below or go to Google Scholar, ResearchGate.

Mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems

The major economies in the world all have set their target for net zero carbon emission. To achieve this goal, the electricity capacity needs to be expanded in the next 30 years under high renewable penetration. We propose a mathematical model and several solution techniques for expanding the capacity in the Texas region.

Li, C., A.J. Conejo, P. Liu, B.P. Omell, J.D. Siirola, I.E. Grossmann.

European Journal of Operations Research(2021)

Paper Preprint Slides

On representative day selection for capacity expansion planning of power systems under extreme events

Renewable generation and load demand can vary significantly from day to day. To capture the variations of renewable and improve the reliability of the power systems, we propose machine learning-based methods for selecting some representative days in the capacity expansion planning model. The inclusion of the extreme events reduce the risk of blackouts in power systems planning.

Li, C., A.J. Conejo, J.D. Siirola, I.E. Grossmann

Under Review in Energy(2021)

Preprint

Shale gas pad development planning under price uncertainty

Natural gas price has high volatility and is challenging to have an accurate forecast. Upstream developers in the natural gas industry always face the uncercertainty in the natural gas price. A low natural gas price can make it unprofitable to develop wells. We solve this problem by developing a stochastic programming framework to help upstream operators make scheduling decisions on their wellpad under high uncertainty of natural gas price.

Li, C., Eason, J. P., Drouven, M. G., & Grossmann, I. E.

AIChE Journal, 66(6), e16933(2020)

Paper Preprint Bibtex Slides

A generalized Benders decomposition-based branch and cut algorithm for two-stage stochastic programs with nonconvex constraints and mixed-binary first and second stage variables

Solving nonconvex two-stage stochastic mixed-integer nonlinear programing problems is challenging due to the nonconvex second stage problem. We propose an efficient algorithm for solving such problem with applications to various problems in the petrochemical and chemical industry.

Li, C., & Grossmann, I. E.

Journal of Global Optimization, 75, 247–272(2019)

Paper Preprint Bibtex Slides

 

Full List

Mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems
Li, C., A.J. Conejo, P. Liu, B.P. Omell, J.D. Siirola, I.E. Grossmann.
European Journal of Operations Research(2021) Paper Preprint Slides

On representative day selection for capacity expansion planning of power systems under extreme events
Li, C., A.J. Conejo, J.D. Siirola, I.E. Grossmann
Under Review in Energy(2021) Preprint

A Review of Stochastic Programming Methods for Optimization of Process Systems Under Uncertainty
Li, C., & Grossmann, I. E.
Frontiers in Chemical Engineering, 2, 34(2021) Paper Preprint Bibtex

Algorithmic Approaches to Inventory Management Optimization
Perez, H. D., Hubbs, C. D., Li, C., & Grossmann, I. E.
Processes, 9(1), 102(2021) Paper Bibtex

Multi-period Design and Planning Model of Shale Gas Field Development.
Peng, Z., Li, C., Grossmann, I. E., Kwon, K., Ko, S., Shin, J., & Feng, Y.
AIChE Journal, e17195(2021) Paper Bibtex

A deep reinforcement learning approach for chemical production scheduling
Hubbs, C. D., Li, C., Sahinidis, N. V., Grossmann, I. E., & Wassick, J. M.
Computers & Chemical Engineering, 141, 106982(2020) Paper Bibtex

Sample average approximation for stochastic nonconvex mixed integer nonlinear programming via outer-approximation
Li, C., Bernal, D. E., Furman, K. C., Duran, M. A., & Grossmann, I. E.
Optimization and Engineering, 1-29(2020) Paper Bibtex

Shale gas pad development planning under price uncertainty
Li, C., Eason, J. P., Drouven, M. G., & Grossmann, I. E.
AIChE Journal, 66(6), e16933(2020) Paper Preprint Bibtex Slides

A generalized Benders decomposition-based branch and cut algorithm for two-stage stochastic programs with nonconvex constraints and mixed-binary first and second stage variables
Li, C., & Grossmann, I. E.
Journal of Global Optimization, 75, 247–272(2019) Paper Preprint Bibtex Slides

A finite ϵ-convergence algorithm for two-stage stochastic convex nonlinear programs with mixed-binary first and second-stage variables
Li, C., & Grossmann, I. E.
Journal of Global Optimization, 75(4), 921-947(2019) Paper Preprint Bibtex Slides

Global Optimization Algorithm for Multi-period Design and Planning of Centralized and Distributed Manufacturing Networks
Lara, C. L., Bernal, D. E., Li, C., & Grossmann, I. E.
Computers & Chemical Engineering, 127, 295-310(2019) Paper Preprint Bibtex

An improved L-shaped method for two-stage convex 0–1 mixed integer nonlinear stochastic programs
Li, C., & Grossmann, I. E.
Computers & Chemical Engineering, 112, 165-179(2018) Paper Preprint Bibtex

Sequence-Based Prediction of Cysteine Reactivity Using Machine Learning
Wang, H., Chen, X., Li, C., Liu, Y., Yang, F., & Wang, C.
Biochemistry, 57(4), 451-460(2018) Paper Bibtex