On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

New development in freefem++

Hecht, F. (2012) · Journal of Numerical Mathematics · doi:10.1515/jnum-2012-0013 · Cited by 3,500 · see citing works

Topology optimization approaches: A comparative review

Sigmund, O., & Maute, K. (2013) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-013-0978-6 · Cited by 2,890 · see citing works

All you need to know about model predictive control for buildings

Drgoňa, J., Arroyo, J., Cupeiro Figueroa, I., Blum, D., Arendt, K., Kim, D., Ollé, E. P., Oravec, J., Wetter, M., Vrabie, D. L., et al. (2020) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2020.09.001 · Cited by 1,020 · see citing works

A statistical approach for inferring the 3D structure of the genome

Varoquaux, N., Ay, F., Noble, W. S., & Vert, J.-P. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu268 · Cited by 246 · see citing works

Stackelberg games for adversarial prediction problems

Brückner, M., & Scheffer, T. (2011) · Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2020408.2020495 · Cited by 229 · see citing works

A unified motion planning method for parking an autonomous vehicle in the presence of irregularly placed obstacles

Li, B., & Shao, Z. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.04.016 · Cited by 195 · see citing works

Scatter search for chemical and bio-process optimization

Egea, J. A., Rodríguez-Fernández, M., Banga, J. R., & Martí, R. (2007) · Journal of Global Optimization · doi:10.1007/s10898-006-9075-3 · Cited by 171 · see citing works

Trimmed constrained mixed effects models: formulations and algorithms

Zheng, P., Barber, R., Sorensen, R. J. D., Murray, C. J. L., & Aravkin, A. Y. (2021) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2020.1868303 · Cited by 174 · see citing works

Evaluation of advanced control strategies for building energy systems

Stoffel, P., Maier, L., Kümpel, A., Schreiber, T., & Müller, D. (2023) · Energy and Buildings · doi:10.1016/j.enbuild.2022.112709 · Cited by 126 · see citing works

Stable task information from an unstable neural population

Rule, M. E., Loback, A. R., Raman, D. V., Driscoll, L. N., Harvey, C. D., & O'Leary, T. (2020) · eLife · doi:10.7554/elife.51121 · Cited by 106 · see citing works

Modelling of light and temperature influences on cyanobacterial growth and biohydrogen production

Zhang, D., Dechatiwongse, P., del Rio-Chanona, E. A., Maitland, G. C., Hellgardt, K., & Vassiliadis, V. S. (2015) · Algal Research · doi:10.1016/j.algal.2015.03.015 · Cited by 84 · see citing works

Field test of Model Predictive Control in residential buildings for utility cost savings

Wang, D., Chen, Y., Wang, W., Gao, C., & Wang, Z. (2023) · Energy and Buildings · doi:10.1016/j.enbuild.2023.113026 · Cited by 84 · see citing works

Dynamic Walking with Compliance on a Cassie Bipedal Robot

Reher, J., Ma, W.-L., & Ames, A. D. (2019) · 2019 18th European Control Conference (ECC) · doi:10.23919/ecc.2019.8796090 · Cited by 81 · see citing works

Machine learning for high-dimensional dynamic stochastic economies

Scheidegger, S., & Bilionis, I. (2019) · Journal of Computational Science · doi:10.1016/j.jocs.2019.03.004 · Cited by 72 · see citing works

Bioprocess modelling of biohydrogen production by Rhodopseudomonas palustris: Model development and effects of operating conditions on hydrogen yield and glycerol conversion efficiency

Zhang, D., Xiao, N., Mahbubani, K. T., del Rio-Chanona, E. A., Slater, N. K. H., & Vassiliadis, V. S. (2015) · Chemical Engineering Science · doi:10.1016/j.ces.2015.02.045 · Cited by 67 · see citing works

AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild

Joska, D., Clark, L., Muramatsu, N., Jericevich, R., Nicolls, F., Mathis, A., Mathis, M. W., & Patel, A. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra48506.2021.9561338 · Cited by 66 · see citing works

Quantum annealing applications, challenges and limitations for optimisation problems compared to classical solvers

Quinton, F. A., Myhr, P. A. S., Barani, M., Crespo del Granado, P., & Zhang, H. (2025) · Scientific Reports · doi:10.1038/s41598-025-96220-2 · Cited by 46 · see citing works

Dynamic Simulation and Optimization for <i>Arthrospira platensis</i> Growth and C-Phycocyanin Production

del Rio-Chanona, E. A., Zhang, D., Xie, Y., Manirafasha, E., & Jing, K. (2015) · Industrial &amp; Engineering Chemistry Research · doi:10.1021/acs.iecr.5b03102 · Cited by 44 · see citing works

An optimal experimental design approach to model discrimination in dynamic biochemical systems

Skanda, D., & Lebiedz, D. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq074 · Cited by 42 · see citing works

Integrating parameter selection with experimental design under uncertainty for nonlinear dynamic systems

Chu, Y., & Hahn, J. (2008) · AIChE Journal · doi:10.1002/aic.11562 · Cited by 41 · see citing works

Optimal Operation Strategy for Biohydrogen Production

del Rio-Chanona, E. A., Dechatiwongse, P., Zhang, D., Maitland, G. C., Hellgardt, K., Arellano-Garcia, H., & Vassiliadis, V. S. (2015) · Industrial &amp; Engineering Chemistry Research · doi:10.1021/acs.iecr.5b00612 · Cited by 38 · see citing works

Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors

Zhang, D., Dechatiwongse, P., del Rio‐Chanona, E. A., Maitland, G. C., Hellgardt, K., & Vassiliadis, V. S. (2015) · Biotechnology and Bioengineering · doi:10.1002/bit.25661 · Cited by 33 · see citing works

Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods

Fioretto, F., Mak, T. W. K., & Van Hentenryck, P. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i01.5403 · Cited by 29 · see citing works

Robust optimal design of experiments for model discrimination using an interactive software tool

Stegmaier, J., Skanda, D., & Lebiedz, D. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055723 · Cited by 15 · see citing works

Interpretable Goal-based Prediction and Planning for Autonomous Driving

Albrecht, S. V., Brewitt, C., Wilhelm, J., Gyevnar, B., Eiras, F., Dobre, M., & Ramamoorthy, S. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra48506.2021.9560849 · Cited by 12 · see citing works

Practical approximations and heuristic approaches for managing shiftable loads in the multi-period optimal power flow framework

Avramidis, I.-I., Capitanescu, F., & Deconinck, G. (2021) · Electric Power Systems Research · doi:10.1016/j.epsr.2020.106864 · Cited by 9 · see citing works

Congestion mitigation in unbalanced residential networks with OPF-based demand management

Vanin, M., Van Acker, T., Ergun, H., D’hulst, R., Vanthournout, K., & Van Hertem, D. (2022) · Sustainable Energy, Grids and Networks · doi:10.1016/j.segan.2022.100936 · Cited by 7 · see citing works

Tire Particle Control with Comfort Bounds for Electric Vehicles

Singer, G., Adelberger, D., Shorten, R., & Re, L. D. (2021) · 2021 60th IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc45484.2021.9682805 · Cited by 6 · see citing works

Phased Long Short-Term Memory-Based Predictive Control of Chemical Processes With Asynchronous and Delayed Measurements

Wu, W., Wang, Y., Zhang, H., Zhang, M.-Q., Chiu, M.-S., & Wu, Z. (2025) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2025.3587908 · Cited by 3 · see citing works

Chance constrained day-ahead robust flexibility needs assessment for low voltage distribution network

Hashmi, M. U., Koirala, A., Ergun, H., & Van Hertem, D. (2022) · arXiv · doi:10.48550/arxiv.2207.10234 · Cited by 1 · see citing works