Mathematical Programming Computation, Volume 13, Issue 2, June 2021
Minotaur: a mixed-integer nonlinear optimization toolkit
Ashutosh Mahajan, Sven Leyffer, Todd Munson, Jeff Linderoth, James Luedtke, Todd Munson
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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