Abstract
We study a particular class of online quadratic optimization problems, where the objective function linearly depends on some time-varying parameters. In the context of prediction-correction algorithms, that is, algorithms that combine a prediction of the future cost function and a correction on the observation of the past one, we explore the effect of a stochastic disturbance in the prediction. We then propose an algorithm that leverages the information on the prediction uncertainty and on the problem structure to approximate the optimal combination between prediction and correction.
Original language | English |
---|---|
Title of host publication | Proceedings of the 25th International Conference on System Theory, Control and Computing, ICSTCC 2021 |
Editors | Lavinia Ferariu, Mihaela-Hanako Matcovschi, Florina Ungureanu |
Publisher | IEEE |
Pages | 138-143 |
ISBN (Electronic) | 978-1-6654-1496-8 |
DOIs | |
Publication status | Published - 2021 |
Event | 25th International Conference on System Theory, Control and Computing, ICSTCC 2021 - Iasi, Romania Duration: 20 Oct 2021 → 23 Oct 2021 |
Conference
Conference | 25th International Conference on System Theory, Control and Computing, ICSTCC 2021 |
---|---|
Country/Territory | Romania |
City | Iasi |
Period | 20/10/21 → 23/10/21 |
Keywords
- optimization
- quadratic programming
- uncertainty