Robert L. Gottwald

TL;DR: The SCIP Optimization Suite 5.0 as discussed by the authors is the latest version of the constraint integer programming solver SCIP for solving mixed-integer linear and nonlinear programs, and it is about 41 % faster than SCIP 4.0 and over twice as fast on instances that take at least 100 seconds to solve.

TL;DR: The SCIP Optimization Suite as discussed by the authors provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP, which includes the MIP and MINLP core with new primal heuristics and a new selection criterion for cutting planes.

TL;DR: The SCIP Optimization Suite as mentioned in this paper is a collection of optimization software that consists of the branch-cut-and-price framework and mixed-integer programming solver SCIP, the Linear Programming solver SoPlex, the modeling language Zimpl, the parallelization framework UG, and the generic GCG.

TL;DR: In this paper, the authors introduce distributed domain propagation, a technique that shares bound tightenings across solvers to trigger further domain propagations, and investigate its impact in modern mixed-integer programming (MIP) and boolean satisfiability problem (SAT) solvers.

TL;DR: This paper investigates "algorithm selection", the task of choosing among a set of algorithms the ones that are likely to perform best for a particular instance of MIP, and treats different parameter settings of the MIP solver SCIP as different algorithms to choose from.