An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization

Emilio Benenati; Sergio Grammatico

doi:10.1109/ICSTCC52150.2021.9607070

An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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	https://doi.org/10.1109/ICSTCC52150.2021.9607070
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

Access to Document

10.1109/ICSTCC52150.2021.9607070

Cite this

@inproceedings{67f54652016a4933b270f61a5ae03beb,

title = "An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization",

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.",

keywords = "optimization, quadratic programming, uncertainty",

author = "Emilio Benenati and Sergio Grammatico",

year = "2021",

doi = "10.1109/ICSTCC52150.2021.9607070",

language = "English",

pages = "138--143",

editor = "Lavinia Ferariu and Mihaela-Hanako Matcovschi and Florina Ungureanu",

booktitle = "Proceedings of the 25th International Conference on System Theory, Control and Computing, ICSTCC 2021",

publisher = "IEEE",

address = "United States",

note = "25th International Conference on System Theory, Control and Computing, ICSTCC 2021 ; Conference date: 20-10-2021 Through 23-10-2021",

}

Benenati, E & Grammatico, S 2021, An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization. in L Ferariu, M-H Matcovschi & F Ungureanu (eds), Proceedings of the 25th International Conference on System Theory, Control and Computing, ICSTCC 2021 . IEEE, pp. 138-143, 25th International Conference on System Theory, Control and Computing, ICSTCC 2021, Iasi, Romania, 20/10/21. https://doi.org/10.1109/ICSTCC52150.2021.9607070

An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization. / Benenati, Emilio ; Grammatico, Sergio.
Proceedings of the 25th International Conference on System Theory, Control and Computing, ICSTCC 2021 . ed. / Lavinia Ferariu; Mihaela-Hanako Matcovschi; Florina Ungureanu. IEEE, 2021. p. 138-143.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization

AU - Benenati, Emilio

AU - Grammatico, Sergio

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - optimization

KW - quadratic programming

KW - uncertainty

UR - http://www.scopus.com/inward/record.url?scp=85123306388&partnerID=8YFLogxK

U2 - 10.1109/ICSTCC52150.2021.9607070

DO - 10.1109/ICSTCC52150.2021.9607070

M3 - Conference contribution

AN - SCOPUS:85123306388

SP - 138

EP - 143

BT - Proceedings of the 25th International Conference on System Theory, Control and Computing, ICSTCC 2021

A2 - Ferariu, Lavinia

A2 - Matcovschi, Mihaela-Hanako

A2 - Ungureanu, Florina

PB - IEEE

T2 - 25th International Conference on System Theory, Control and Computing, ICSTCC 2021

Y2 - 20 October 2021 through 23 October 2021

ER -

An Adaptive Convex Combination between Prediction and Correction in Online Quadratic optimization

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this