| Efficient stochastic programming in Julia M Biel, M Johansson INFORMS Journal on Computing 34 (4), 1885-1902, 2022 | 20 | 2022 |
| Dynamic cut aggregation in L-shaped algorithms M Biel, M Johansson arXiv preprint arXiv:1910.13752, 2019 | 7 | 2019 |
| Efficient trajectory reshaping in a dynamic environment M Biel, M Norrlöf 2018 IEEE 15th International Workshop on Advanced Motion Control (AMC), 54-59, 2018 | 6 | 2018 |
| Optimal day-ahead orders using stochastic programming and noise-driven recurrent neural networks M Biel 2021 IEEE Madrid PowerTech, 1-6, 2021 | 5 | 2021 |
| Distributed L-shaped algorithms in Julia M Biel, M Johansson 2018 IEEE/ACM Parallel Applications Workshop, Alternatives To MPI (PAW-ATM …, 2018 | 4 | 2018 |
| POLO. Jl: Policy-based optimization algorithms in Julia M Biel, A Aytekin, M Johansson Advances in Engineering Software 136, 102695, 2019 | 3 | 2019 |
| POLO: a POLicy-based Optimization library A Aytekin, M Biel, M Johansson arXiv preprint arXiv:1810.03417, 2018 | 3 | 2018 |
| A Fast Smoothing Procedure for Large-Scale Stochastic Programming M Biel, VV Mai, M Johansson 2021 60th IEEE Conference on Decision and Control (CDC), 2394-2399, 2021 | | 2021 |
| Large-scale hydropower models in StochasticPrograms. jl M Biel arXiv preprint arXiv:2111.02099, 2021 | | 2021 |
| Distributed Stochastic Programming with Applications to Large-Scale Hydropower Operations M Biel KTH Royal Institute of Technology, 2019 | | 2019 |
| Sensor-Based Trajectory Optimization M Biel | | 2016 |
| SiMpLIfy: A toolbox for structured model reduction M Biel, F Farokhi, H Sandberg 2015 European Control Conference (ECC), 1159-1164, 2015 | | 2015 |
