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Kim, Youngdae
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MINLP formulations for continuous piecewise linear function fitting

Author(s)
Goldberg, NoamRebennack, SteffenKim, YoungdaeKrasko, VitaliyLeyffer, Sven
Issued Date
2021-05
DOI
10.1007/s10589-021-00268-5
URI
https://scholarworks.unist.ac.kr/handle/201301/83404
Citation
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, v.79, no.1, pp.223 - 233
Abstract
We consider a nonconvex mixed-integer nonlinear programming (MINLP) model proposed by Goldberg et al. (Comput Optim Appl 58:523-541, 2014. ) 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.
Publisher
SPRINGER
ISSN
0926-6003
Keyword (Author)
ReformulationMixed-integer nonlinear programLinear spline regressionBranch-and-bound

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