Technical Reports & Book Chapters

  1. Jiang, S., Qin, S., Pulsipher, J. and Zavala V.M (2022). Convolutional Neural Networks: Basic Concepts and Applications in Manufacturing. [link]

  2. Shin, S., Lu, Q., and Zavala, V.M. Unifying Theorems for Subspace Identification and Dynamic Mode Decomposition, Technical Report, 2020. [link]

  3. Jalving, J., & Zavala, V. M. (2019). Optimization in Chemical and Biological Engineering using Julia. In Introduction to Software for Chemical Engineers (pp. 713-732). CRC Press. [pdf]

  4. Shin, S. and Zavala, V.M. Computing Economic-Optimal and Stable Equilibria for Droop-Controlled Microgrids, 2018. [link]

  5. Martin-Hernandez, E., Sampat, A. M., Martin, M., Zavala, V. M., and Ruiz-Mercado, G. J. A Logistics Analysis for Advancing Carbon and Nutrient Recovery from Organic Waste. In Advances in Carbon Management Technologies, pp. 186-207, 2020. [link]

  6. Cao, Y., and Zavala, V.M. A Sigmoidal Approximation for Chance-Constrained Nonlinear Programs, 2018. [link]

  7. Shin, S. and Zavala, V.M. Multi-Grid Schemes for Multi-Scale Control of Energy Systems. In Sean Meyn, Tariq Samad, Ian Hiskens, and Jakob Stoustrup ed. Energy Markets and Responsive Grids, Springer, 2018. [link]

  8. Larson, R., Sharara, M., Good, L., Porter, T., Zavala, V.M., Sampat, A. and Smith, A. Evaluation of Manure Storage Capital Projects in the Yahara River Watershed. Technical Report for Dane County, WI, 2016. [pdf]

  9. Chiang N.Y.; and Zavala V.M. Emerging Optimal Control Models and Solvers for Interconnected Natural Gas and Electricity Networks. In Martín, M., ed. Alternative Energy Sources and Technologies: Process Design and Operation. Springer, 2016. [link]

  10. Zavala, V. M. Managing Conflicts among Decision-Makers in Multiobjective Design and Operations. In Ruiz-Mercado, G. and Cabezas, H., ed. Sustainability in the Design, Synthesis and Analysis of Chemical Engineering Processes, Elsevier, 2016. [link]

  11. Kim, K. and Zavala V.M. Large-Scale Stochastic Mixed-Integer Programming Algorithms for Power Generation Scheduling. In Martín, M., ed. Alternative Energy Sources and Technologies: Process Design and Operation. Springer, 2016. [link]

  12. Zavala, V. M.; and Biegler, L.T. Nonlinear Programming Strategies for State Estimation and Model Predictive Control. In Nonlinear Model Predictive Control, pp. 419-432, Springer-Verlag, Berlin, 2009. [link]