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Gurobi Optimizer v7.5 delivers higher performance, new capabilities

The Gurobi Optimizer v7.5 extends Gurobi’s tradition of providing significant performance enhancements with each new release. The overall performance improvements from v7.0 on models that take more than one second to solve include:

MIP: 32 percent faster (70 percent faster on models that take >100 seconds to solve)

LP: Concurrent: 15 percent faster (47 percent faster on models that take >100 seconds to solve); Dual Simplex: 19 percent faster (4 percent faster on models that take >100 seconds to solve); Barrier: 9 percent faster (34 percent faster on models that take >100 seconds to solve)

MIQP: 220 percent faster (too few models >100s to compare)

SOCP: 17 percent faster (too few models >100s to compare)

Gurobi’s Python modeling interface has been extended to further simplify the task of translating mathematical models into efficient implementations. This version contains new, simplified syntax for specifying general constraints (min, max, abs, and, or, and indicator), and for range constraints.

Gurobi’s multi-objective interface has been greatly simplified. You can now specify objectives through a single setObjectiveN routine.

Gurobi’s new multi-objective environments feature allows you to set termination parameters for each pass of the multi-objective optimization algorithm separately.

Gurobi has tightened its internal tolerances for MIQP models to reduce the number of cases where the solution exhibits small constraint violations.

Other improvements include:

  • Java interface now includes a JavaDoc version of r documentation.
  • Added support for Python 3.6 (including Anaconda 3.6) on Linux, Mac and Windows, as well as support for R 3.4.
  • Added support for Visual Studio 2017 on Windows.

With version 7.5, Gurobi continues to show its commitment to providing the best solvers, features, and support to help O.R. professionals succeed with optimization. For more information, visit

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