The SCIP Optimization Suite
SCIP is currently one of the fastest non-commercial solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP). It is also a framework for constraint integer programming and branch-cut-and-price. It allows for total control of the solution process and the access of detailed information down to the guts of the solver.
By default, SCIP comes with a bouquet of different plugins for solving MIPs and MINLPs.
This channel is contains talks about SCIP, different applications where SCIP has been used, and tutorials about how to use SCIP.
Windows Installation of GCG and the SCIP Optimization Suite (Tutorial)
Linux (Ubuntu) Installation of GCG and the SCIP Optimization Suite (Tutorial)
Git Installation of GCG and the SCIP Optimization Suite (Tutorial)
Question and Answer Session - PySCIPOpt: The Python interface for SCIP Optimization Suite
Question and Answer Session - MINLP
Parameterizing branch-and-bound search trees to learn branching policies
Plenary Talk - Decomposition approaches for a large-scale scheduling problem
Introduction to SCIP 7.0
Question and Answer Session - Benders' Decomposition
PaPILO - Parallel Presolve for Integer and Linear Optimization
Mixed-Integer Programming Techniques for the Connected Max-k-Cut Problem
Using SCIP as a branch-and-price framework to solve the train timetable rescheduling problem