TY  - JOUR
U1  - Wissenschaftlicher Artikel
A1  - Mahajan, Ashutosh
A1  - Leyffer, Sven
A1  - Linderoth, Jeff
A1  - Luedtke, James
A1  - Munson, Todd
T1  - Minotaur: a mixed-integer nonlinear optimization toolkit
JF  - Mathematical Programming Computation
N2  - 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.
AB  - 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.
KW  - Software
KW  - Theoretical Computer Science
Y1  - 2020
SN  - 1867-2949
SS  - 1867-2949
U6  - https://doi.org/10.1007/s12532-020-00196-1
DO  - https://doi.org/10.1007/s12532-020-00196-1
VL  - 13
IS  - 2
SP  - 301
EP  - 338
S1  - 38
PB  - Springer Science and Business Media LLC
ER  -