A review and comparison of solvers for convex MINLP
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In this paper a review of deterministic software for solving convex MINLP problems as well as a comprehensive comparison of a large selection of commonly available solvers are presented. A summary of the most common methods for solving convex MINLP problems is given to better highlight the differences between the solvers. The results also provide guidelines on how well suited a specific solver or method is for particular types of MINLP problems.
Type:
Scientific Paper
Area:
Optimization
Target Group:
Basic
DOI:
https://doi.org/10.1007/s11081-018-9411-8
Cite as:
Kronqvist, J., Bernal, D.E., Lundell, A. et al. A review and comparison of solvers for convex MINLP. Optim Eng 20, 397–455 (2019)
Author of the review:
Ivo Nowak
HAW Hamburg
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Eligius Hendrix
The analysis is very systematic. The first author is a very good investigator. The character of the paper I like is the insght into what kind of methds are best fit for whcih types of problems.