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Gurobi introduces Gurobi Optimizer v7.0

Gurobi Optimization recently introduced Gurobi Optimizer v7.0, with higher performance and powerful new modeling capabilities.

Some of the enhancements and new features include:

  • Significant performance improvements across MIP, LP, QCP, MIQCP and MIQP problem types.
  • Python modeling enhancements, including new methods and classes that further simplify the task of translating mathematical models into efficient implementations.
  • Support for multiple objectives, allowing users to associate multiple, independent optimization objectives with their model and then perform either blended or lexicographic optimization on the resulting multi-objective model.
  • MIP solution pool support, so users can obtain more than just one optimal solution to an MIP model.
  • General constraints, so users can enter commonly occurring constraints (MIN/MAX, ABS, AND/OR and Indicator constraints) without having to translate them into linear constraints.
  • Support for tuning criterion, so users can search for settings that produce the best lower bound, upper bound or gap.

In addition, Gurobi has added support for Python 3.5 on the Mac, enhanced its .NET property support and added a number of useful new parameters.

For more information, visit


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2018 INFORMS Conference on Business Analytics and Operations Research
April 15-17, 2018, Baltimore


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