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arxiv: 2112.08872 · v1 · pith:YE5RDMGSnew · submitted 2021-12-16 · 🧮 math.OC

The SCIP Optimization Suite 8.0

classification 🧮 math.OC
keywords scipoptimizationsuiteaddedframeworkimprovementsmajoradditional
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The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 8.0 of the SCIP Optimization Suite. Major updates in SCIP include improvements in symmetry handling and decomposition algorithms, new cutting planes, a new plugin type for cut selection, and a complete rework of the way nonlinear constraints are handled. Additionally, SCIP 8.0 now supports interfaces for Julia as well as Matlab. Further, UG now includes a unified framework to parallelize all solvers, a utility to analyze computational experiments has been added to GCG, dual solutions can be postsolved by PaPILO, new heuristics and presolving methods were added to SCIP-SDP, and additional problem classes and major performance improvements are available in SCIP-Jack.

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  1. RL-SPH: Learning to Achieve Feasible Solutions for Integer Linear Programs

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    RL-SPH is a reinforcement learning start primal heuristic that independently produces feasible solutions for ILPs with non-binary integers at 100% rate and with 28.6× lower primal gap than prior start heuristics.