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Minotaur: a mixed-integer nonlinear optimization toolkit

delete2020-11-07
delete6
PRE
AI
A
Ashutosh Mahajan *
S
Sven Leyffer
J
Jeff Linderoth
J
James Luedtke
T
Todd Munson
DOI:10.1007/s12532-020-00196-1delete
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摘要

摘要

En 中文
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.
Keyword:
Mixed-integer nonlinear programming
Global optimization
Software
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期刊

Mathematical Programming Computation 封面图
Mathematical Programming Computation
IF:
3.6
论文数:
201
被引数:
1.9K

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U
united states department of energy (doe)
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11.3W
论文数: 9.6W
被引数: 246
I
indian institute of technology system (iit system)
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9.5W
论文数: 9.9W
被引数: 93
I
indian institute of technology (iit) - bombay
学者数:
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论文数: 5.6K
被引数: 0
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