Monday, 16:15 - 16:40 h, Room: MA 005

 

Ambros Gleixner
Rapid optimality-based bound tightening

Coauthors: Timo Berthold, Stefan Weltge

 

Abstract:
Optimality-based bound tightening (OBBT) is a well-known, simple, yet computationally expensive procedure to reduce variable domains of mixed-integer nonlinear programs (MINLPs) by solving a series of auxiliary linear programs (LPs). We present techniques to reduce the computational effort incurred by OBBT and exploit dual information from the LP solutions during a subsequent branch-and-bound solution process. We evaluate the performance impact of these techniques using an implementation within the MINLP solver SCIP.

 

Talk 3 of the invited session Mon.3.MA 005
"Tight relaxations" [...]
Cluster 14
"Mixed-integer nonlinear programming" [...]

 

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