26 February 2024 | Suresh Bolusani, Mathieu Besançon, Ksenia Bestuzheva, Antonia Chmiela, João Dionísio, Tim Donkiewicz, Jasper van Doornmalen, Leon Eifler, Mohammed Ghannam, Ambros Gleixner, Christoph Graczyk, Katrin Halbig, Ivo Hédtk, Alexander Hoen, Christopher Hojny, Rolf van der Hulst, Dominik Kamp, Thorsten Koch, Kevin Kofler, Jurgen Lentz, Julian Manns, Gioni Mexi, Erik Mühmer, Marc E. Pfetsch, Franziska Schlösser, Felipe Serrano, Yuji Shinano, Mark Turner, Stefan Vigerske, Dieter Weninger, Liding Xu
The SCIP Optimization Suite 9.0 is an updated version of the software suite for mathematical optimization, centered around the constraint integer programming (CIP) framework SCIP. This report discusses the enhancements and extensions included in version 9.0, which include improved symmetry handling, additions and improvements to nonlinear handlers and primal heuristics, a new cut generator and selection schemes, a new branching rule, a new LP interface, and several bug fixes. The suite also features new Rust and C++ interfaces for SCIP, a new Python interface for SoPLEX, and enhancements to existing interfaces. Improvements to the LP solver SoPLEX, presolving library PAPILO, parallel framework UG, decomposition framework GCG, and the SCIP extension SCIP-SDP are also highlighted. These additions and enhancements have resulted in overall performance improvements in solving time, number of nodes in the branch-and-bound tree, and solver reliability. The report is structured into three main parts: performance improvements, core improvements, and improvements to other components and interfaces.The SCIP Optimization Suite 9.0 is an updated version of the software suite for mathematical optimization, centered around the constraint integer programming (CIP) framework SCIP. This report discusses the enhancements and extensions included in version 9.0, which include improved symmetry handling, additions and improvements to nonlinear handlers and primal heuristics, a new cut generator and selection schemes, a new branching rule, a new LP interface, and several bug fixes. The suite also features new Rust and C++ interfaces for SCIP, a new Python interface for SoPLEX, and enhancements to existing interfaces. Improvements to the LP solver SoPLEX, presolving library PAPILO, parallel framework UG, decomposition framework GCG, and the SCIP extension SCIP-SDP are also highlighted. These additions and enhancements have resulted in overall performance improvements in solving time, number of nodes in the branch-and-bound tree, and solver reliability. The report is structured into three main parts: performance improvements, core improvements, and improvements to other components and interfaces.