| A review and comparison of solvers for convex MINLP J Kronqvist, DE Bernal, A Lundell, IE Grossmann Optimization and Engineering 20, 397-455, 2019 | 230 | 2019 |
| Efficient verification of relu-based neural networks via dependency analysis E Botoeva, P Kouvaros, J Kronqvist, A Lomuscio, R Misener Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3291-3299, 2020 | 84 | 2020 |
| The extended supporting hyperplane algorithm for convex mixed-integer nonlinear programming J Kronqvist, A Lundell, T Westerlund Journal of Global Optimization 64, 249-272, 2016 | 82 | 2016 |
| Structural learning in artificial neural networks using sparse optimization M Manngård, J Kronqvist, JM Böling Neurocomputing 272, 660-667, 2018 | 41 | 2018 |
| Partition-based formulations for mixed-integer optimization of trained relu neural networks C Tsay, J Kronqvist, A Thebelt, R Misener Advances in Neural Information Processing Systems 34, 3068-3080, 2021 | 29 | 2021 |
| Reformulations for utilizing separability when solving convex MINLP problems J Kronqvist, A Lundell, T Westerlund Journal of Global Optimization 71, 571-592, 2018 | 29 | 2018 |
| Using regularization and second order information in outer approximation for convex MINLP J Kronqvist, DE Bernal, IE Grossmann Mathematical Programming 180 (1-2), 285-310, 2020 | 23 | 2020 |
| A center-cut algorithm for quickly obtaining feasible solutions and solving convex MINLP problems J Kronqvist, DE Bernal, A Lundell, T Westerlund Computers & Chemical Engineering 122, 105-113, 2019 | 20 | 2019 |
| ENTMOOT: a framework for optimization over ensemble tree models A Thebelt, J Kronqvist, M Mistry, RM Lee, N Sudermann-Merx, R Misener Computers & Chemical Engineering 151, 107343, 2021 | 19 | 2021 |
| Method for solving generalized convex nonsmooth mixed-integer nonlinear programming problems VP Eronen, J Kronqvist, T Westerlund, MM Mäkelä, N Karmitsa Journal of Global Optimization 69, 443-459, 2017 | 16 | 2017 |
| The supporting hyperplane optimization toolkit–a polyhedral outer approximation based convex MINLP solver utilizing a single branching tree approach A Lundell, J Kronqvist, T Westerlund Preprint, Optimization Online, 2018 | 14 | 2018 |
| Maximizing information from chemical engineering data sets: applications to machine learning A Thebelt, J Wiebe, J Kronqvist, C Tsay, R Misener Chemical Engineering Science 252, 117469, 2022 | 12 | 2022 |
| A center-cut algorithm for solving convex mixed-integer nonlinear programming problems J Kronqvist, A Lundell, T Westerlund Computer Aided Chemical Engineering 40, 2131-2136, 2017 | 11 | 2017 |
| Between steps: Intermediate relaxations between big-M and convex hull formulations J Kronqvist, R Misener, C Tsay Integration of Constraint Programming, Artificial Intelligence, and …, 2021 | 10 | 2021 |
| SHOT–A global solver for convex MINLP in Wolfram Mathematica A Lundell, J Kronqvist, T Westerlund Computer aided chemical engineering 40, 2137-2142, 2017 | 9 | 2017 |
| A disjunctive cut strengthening technique for convex MINLP J Kronqvist, R Misener Optimization and Engineering 22 (3), 1315-1345, 2021 | 8 | 2021 |
| A Review and Comparison of Solvers for Convex MINLP, vol. 20 J Kronqvist, DE Bernal, A Lundell, IE Grossmann Springer, US., 2019 | 8 | 2019 |
| Global optimization with ensemble machine learning models A Thebelt, J Kronqvist, RM Lee, N Sudermann-Merx, R Misener Computer Aided Chemical Engineering 48, 1981-1986, 2020 | 7 | 2020 |
| Improvements to the supporting hyperplane optimization toolkit solver for convex MINLP A Lundell, J Kronqvist, T Westerlund XIII Global Optimization Workshop GOW 16, 101-104, 2016 | 6 | 2016 |
| On solving nonconvex MINLP problems with SHOT A Lundell, J Kronqvist Optimization of Complex Systems: Theory, Models, Algorithms and Applications …, 2019 | 5 | 2019 |
Andreas LundellSenior Lecturer, Information Technology, Åbo Akademi UniversityVerifierad e-postadress på abo.fi
