November 7, 2018, Beaverton, OR - At the INFORMS 2018 Annual Meeting Gurobi workshop and in the corresponding marketing material, including a Twitter post, we published analytics claiming Gurobi was faster, as compared to CPLEX and Xpress, than it actually is. The figures reported in those publications were incorrect, and we retract those statements in full.
We phrased our messaging in a way that suggests that the 99 models we were using are the official MIPLIB 2017 benchmark set. The models we used are, however, only a subset of the larger benchmark set, and this subset was selected by us. We thought that our subset selection was fair, but now realize that it was not. We apologize to the MIPLIB 2017 committee for this fundamental error in our analytic approach.
In addition, we attributed our experiment to Prof. Hans Mittelmann in such a way that it gives the clear impression of being an independent analysis. This is inaccurate. Prof. Mittelmann only produced the log files, which we then used to extract the results that we reported. We apologize to Prof. Mittelmann for this misleading characterization of his involvement in our flawed analysis.
In addition, we apologize to IBM CPLEX and FICO Xpress, for unfairly representing the performance of their respective products.
We would like to thank our competitors for the gracious way in which they have handled this matter by simply bringing it to the attention of the MIP community as a whole rather than trying to leverage it against us. We are grateful that, in spite of the fierce competition between vendors, this industry follows and maintains high scientific and ethical standards. Our performance in this instance fell below those standards, which we sincerely regret. We will strive to do better and to avoid making errors like this in the future.
Gurobi (www.gurobi.com) is in the business of helping companies make better decisions through the use of prescriptive analytics. In addition to providing the best math programming solver, as well as tools for distributed optimization and optimization in the cloud, the company is known for its outstanding support and straightforward pricing.
The Gurobi Optimizer is a state-of-the-art solver for linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), mixed-integer linear programming (MILP), mixed-integer quadratic programming (MIQP), and mixed-integer quadratically constrained programming (MIQCP). Gurobi was designed from the ground up to exploit modern architectures and multi-core processors, using the most advanced implementations of the latest algorithms. Founded in 2008, Gurobi Optimization is based in Beaverton, OR (+1 713 871 9341).
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