We present a new toolkit for solving mixed-integer nonlinear optimization problems, called MINOTAUR. The MINOTAUR toolkit is designed to provide a flexible and efficient framework for solving MINLPs. The code is developed in a modular way to enable developers and users to efficiently combine the knowledge of problem structure with algorithmic insights. We will survey recent developments in MINLP and present the underlying algorithmic ideas of MINOTAUR. Our talk will focus on the integration of nonlinear solvers into the MINOTAUR’s branch-and-cut framework, and highlight challenges and opportunities for nonlinear optimization.
Questions? Please Contact Coordinator: Lulu Kang, Assistant Professor via email: firstname.lastname@example.org
Refreshments will be served in Building E1 112
|Wed Apr 11, 2012 4:40pm – 5:40pm Central Time|
|Life Sciences Room 152 (map)|