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 linea...

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Veröffentlicht in:Computational optimization and applications 2021-05, Vol.79 (1), p.223-233
Hauptverfasser: Goldberg, Noam, Rebennack, Steffen, Kim, Youngdae, Krasko, Vitaliy, Leyffer, Sven
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Sprache:eng
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Zusammenfassung: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.
ISSN:1573-2894
0926-6003
1573-2894
DOI:10.1007/s10589-021-00268-5