Artikel
MINLP formulations for continuous piecewise linear function fitting
We consider a nonconvex mixed-integer nonlinear programming (MINLP) model proposed by Goldberg et al. (Comput Optim Appl 58:523–541, 2014. https://doi.org/10.1007/s10589-014-9647-y) for piecewise linear function fitting. We show that this MINLP model is incomplete and can result in a piecewise linear curve that is not the graph of a function, because it misses a set of necessary constraints. We provide two counterexamples to illustrate this effect, and propose three alternative models that correct this behavior. We investigate the theoretical relationship between these models and evaluate their computational performance.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Computational Optimization and Applications ; ISSN: 1573-2894 ; Volume: 79 ; Year: 2021 ; Issue: 1 ; Pages: 223-233 ; New York, NY: Springer US
- Klassifikation
-
Mathematik
- Thema
-
Mixed-integer nonlinear program
Linear spline regression
Branch-and-bound
Reformulation
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Goldberg, Noam
Rebennack, Steffen
Kim, Youngdae
Krasko, Vitaliy
Leyffer, Sven
- Ereignis
-
Veröffentlichung
- (wer)
-
Springer US
- (wo)
-
New York, NY
- (wann)
-
2021
- DOI
-
doi:10.1007/s10589-021-00268-5
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Goldberg, Noam
- Rebennack, Steffen
- Kim, Youngdae
- Krasko, Vitaliy
- Leyffer, Sven
- Springer US
Entstanden
- 2021
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