Category: Publications

Stinchfield, G., B.L., Ammari, J. Morgan, J. Siirola, M. Zamarripa, C.D. Laird, “Optimization of Process Families for Improved Deployment of Industrial Decarbonization Processes using Machine Learning Surrogates,” Computer Aided Chemical Engineering, Volume 52, 2023, 1331-1337.

Rodriguez, J. S., Parker, R., Laird, C., Nicholson, B., Siirola, J., & Bynum, M. (2023). Scalable parallel nonlinear optimization with PyNumero and Parapint. INFORMS Journal on Computing, 35(2), 265-517. https://doi.org/10.1287/ijoc.2023.1272

Dabadghao, V., Ghouse, J., Eslick, J., Lee, A., Burgard, A.P., Miller, D., & Biegler, L. (2023). A complementarity-based vapor-liquid equilibrium formulation for equation-oriented simulation and optimization. AIChE Journal, 69 (4). https://doi.org/10.1002/aic.18029

Parker, R., & Biegler, L. T. (2022). Dynamic modeling and nonlinear model predictive control of a moving bed chemical looping combustion reactor. IFAC-PapersOnLine, 55(7), 400-405. https://doi.org/10.1016/j.ifacol.2022.07.476.

Parker, R., Nicholson, B. L., Siirola, J., Laird, C. D., & Biegler, L. T. (2022). An implicit function formulation for nonlinear programming with index-1 differential algebraic equation systems. In Y. Yamashita & M. Kano (Eds.), 14th International Symposium on Process Systems Engineering (PSE2021+), Computer Aided Chemical Engineering, (Vol. 49, pp. 1141-1146). Elsevier. https://doi.org/10.1016/B978-0-323-85159-6.50190-1

Cho, S., Li, C., & Grossmann, I.E. (2022). Recent advances and challenges in optimization models for expansion planning of power systems and reliability optimization. Computers and Chemical Engineering, 165, 1079245. https://doi.org/10.1016/j.compchemeng.2022.107924

Okoli, C. O., Parker, R., Chen, Y., Ostace, A., Lee, A., Bhattacharyya, D., Tong, A., Biegler, L. T., Burgard, A. P., & Miller, D. C. (2022). Application of an equation-oriented framework to the formulation and parameter estimation of chemical looping reaction kinetic models. AIChE Journal 2022, 68(10). https://doi.org/10.1002/aic.17796

Sauk, B., & Sahinidis, N. V. (2022). Hyperparameter tuning of programs with HybridTuner. Annals of Mathematics and Artificial Intelligence, 91, 133–151. https://doi.org/10.1007/s10472-022-09793-3

Eslick, J. C., Zamarripa, M. A., Ma, J., M. Wang, M., Bhattacharya, I., Rychener, B., Pinkston, P., Bhattacharyya, D., Zitney, S. E., Burgard, A. P., & Miller, D. C. (2022). Predictive modeling of an existing subcritical pulverized-coal power plant for optimization: data reconciliation, parameter estimation, and validation. Applied Energy, 319. https://doi.org/10.1016/j.apenergy.2022.119226.