Decison Tree for Optimization Software

Benchmarks for Optimization Software

By Hans Mittelmann (mittelmann at asu.edu)

END OF A BENCHMARKING ERA
For many years our benchmarking effort had included the solvers CPLEX, Gurobi, and XPRESS. Through an action by Gurobi at the 2018 INFORMS Annual Meeting this has come to an end. IBM and FICO demanded that results for their solvers be removed. See here for more details. The resulting void was filled by other developers.
In August 2024 Gurobi decided to withdraw from the benchmarks as well and their results have been removed. On 12/24/2024 MindOpt followed suit.

Note that on top of the benchmarks a link to logfiles is given!

Note also that we do not use performance profiles. See this paper and that one
We use instead the shifted geometric mean

COMBINATORIAL OPTIMIZATION

LINEAR PROGRAMMING
The Simplex and Barrier benchmarks are replaced by benchmarks that show how well solvers find a primal-dual feasible point (as barrier methods in general do) or an optimal basic solution (as simplex methods in general do). Codes do not have to use a textbook version of either method.

MIXED INTEGER LINEAR PROGRAMMING

SEMIDEFINITE/SQL PROGRAMMING

NONLINEAR PROGRAMMING

MIXED INTEGER QPs

MIXED INTEGER QCPs

MIXED INTEGER NONLINEAR PROGRAMMING

PROBLEMS WITH EQUILIBRIUM CONSTRAINTS

This is part of the Decision Tree for Optimization Software

Decision Tree for Optimization Software

Benchmarks for Optimization Software

Note also that we do not use performance profiles. See this paper and that one We use instead the shifted geometric mean

COMBINATORIAL OPTIMIZATION

LINEAR PROGRAMMING

MIXED INTEGER LINEAR PROGRAMMING

SEMIDEFINITE/SQL PROGRAMMING

NONLINEAR PROGRAMMING

MIXED INTEGER QPs

MIXED INTEGER QCPs

MIXED INTEGER NONLINEAR PROGRAMMING

PROBLEMS WITH EQUILIBRIUM CONSTRAINTS

This is part of the Decision Tree for Optimization Software

Note also that we do not use performance profiles. See this paper and that one
We use instead the shifted geometric mean