Publications
Group highlights
(For a full list see below or go to Google Scholar, ResearchGate.
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)
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
International Journal of Electrical Power & Energy Systems(2021)
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)
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)
Full List
Diagnosing Infeasible Optimization Problems Using Large Language Models
Chen, H., Constante-Flores, G., & Li, C.
arXiv preprint(2023)
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Distributed manufacturing for electrified chemical processes in a microgrid
Ramanujam, A., Constante-Flores, G., & Li, C.
AIChE Journal, 69(12), e18265.(2023)
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Recent advances and challenges in optimization models for expansion planning of power systems and reliability optimization
Cho, S., Li, C., & Grossmann, I. E.
Computers & Chemical Engineering, 107924.(2022)
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Bibtex
A Review on the Performance of Linear and Mixed Integer Two-Stage Stochastic Programming Software
Torres, J. J., Li, C., Apap, R. M., & Grossmann, I. E.
Algorithms, 15(4)(2022)
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Bibtex
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)
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Preprint
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Slides
On representative day selection for capacity expansion planning of power systems under extreme operating conditions
Li, C., A.J. Conejo, J.D. Siirola, I.E. Grossmann
International Journal of Electrical Power & Energy Systems(2021)
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Preprint
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Shale gas field development planning under production profile uncertainty
Peng, Z., Li, C., Grossmann, I. E., Kwon, K., Ko, S., Shin, J., & Feng, Y.
AIChE Journal, e17439.(2021)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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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)
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