Global optimization of mixed-integer nonlinear programs with SCIP 8

Abstract For over 10 years, the constraint integer programming framework SCIP has been extended by capabilities for the solution of convex and nonconvex mixed-integer nonlinear programs (MINLPs). With the recently published version 8.0, these capabilities have been largely reworked and extended. This paper discusses the motivations for recent changes and provides an overview of features that are particular to MINLP solving in SCIP. Further, difficulties in benchmarking global MINLP solvers are discussed and a comparison with several state-of-the-art global MINLP solvers is provided.

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Year of publication:	2023
Authors:	Bestuzheva, Ksenia ; Chmiela, Antonia ; Müller, Benjamin ; Serrano, Felipe ; Vigerske, Stefan ; Wegscheider, Fabian
Published in:	Journal of Global Optimization. - New York : Springer US, ISSN 1573-2916. - Vol. 91.2023, 2, p. 287-310
Publisher:	New York : Springer US
Subject:	Global optimization \| Mixed-integer nonlinear programming \| SCIP \| Branch-and-cut \| Optimization software \| Benchmark

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Type of publication:	Article
Type of publication (narrower categories):	Article
Language:	English
Other identifiers:	10.1007/s10898-023-01345-1 [DOI]
Source:	EconStor

Persistent link: https://www.econbiz.de/10015408295