Goal of this project is to produce novel open source software for solving mixed-integer nonlinear programs (MINLP) with convex relaxation. The main objectives of this effort are: ... computational results on the new and other available libraries of test problems.
Keywords for this software
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
- Kılınç, Mustafa R.; Linderoth, Jeff; Luedtke, James: Lift-and-project cuts for convex mixed integer nonlinear programs (2017)
- Puranik, Yash; Sahinidis, Nikolaos V.: Domain reduction techniques for global NLP and MINLP optimization (2017)
- Huang, Kuo-Ling; Mehrotra, Sanjay: An empirical evaluation of a walk-relax-round heuristic for mixed integer convex programs (2015)
- Hijazi, Hassan; Bonami, Pierre; Ouorou, Adam: An outer-inner approximation for separable mixed-integer nonlinear programs (2014)
- Kılınç, Mustafa; Linderoth, Jeff; Luedtke, James; Miller, Andrew: Strong-branching inequalities for convex mixed integer nonlinear programs (2014)
- Melo, Wendel; Fampa, Marcia; Raupp, Fernanda: Integrating nonlinear branch-and-bound and outer approximation for convex mixed integer nonlinear programming (2014)
- Bonami, Pierre; Kilinç, Mustafa; Linderoth, Jeff: Algorithms and software for convex mixed integer nonlinear programs (2012)
- Bonami, Pierre: Lift-and-project cuts for mixed integer convex programs (2011)