Minotaur: a mixed-integer nonlinear optimization toolkit

  • We present a flexible framework for general mixed-integer nonlinear programming (MINLP), called Minotaur, that enables both algorithm exploration and structure exploitation without compromising computational efficiency. This paper documents the concepts and classes in our framework and shows that our implementations of standard MINLP techniques are efficient compared with other state-of-the-art solvers. We then describe structure-exploiting extensions that we implement in our framework and demonstrate their impact on solution times. Without a flexible framework that enables structure exploitation, finding global solutions to difficult nonconvex MINLP problems will remain out of reach for many applications.

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Metadaten
Author:Ashutosh Mahajan, Sven Leyffer, Jeff Linderoth, James Luedtke, Todd Munson
DOI:https://doi.org/10.1007/s12532-020-00196-1
ISSN:1867-2949
Parent Title (English):Mathematical Programming Computation
Publisher:Springer Science and Business Media LLC
Document Type:Article
Language:English
Year of Completion:2020
Tag:Software; Theoretical Computer Science
Volume:13
Issue:2
Page Number:38
First Page:301
Last Page:338
Mathematical Programming Computation :MPC 2021 - Issue 2
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