Highlights of Gurobi Optimizer 7.0

Some of the enhancements and the new features include:

• Significant performance improvements across MIP, LP, QCP, MIQCP and MIQP problem types
• Python Modeling Enhancements — Our Python modeling interface has been greatly enhanced. We provide new methods and classes that further simplify the task of translating mathematical models into efficient implementations.
• Support for Multiple Objectives — You can now associate multiple, independent optimization objectives with your model, and then perform either blended or lexicographic optimization on the resulting multi-objective model.
• MIP Solution Pool Support — You can now obtain more than just one optimal solution to your MIP model. Specifically, you can now request the N best solutions, or N solutions that are less than a specified gap from the optimal solution.
• New General Constraints — You can now enter commonly occurring constraints (MIN/MAX, ABS, AND/OR, and Indicator constraints) without having to translate them into linear constraints.
• Support for Tuning Criterion — In previous releases, the tuning tool would always try to find settings that minimize the optimality gap. You can use the new TuneCriterion parameter to search for settings that produce the best lower bound, upper bound, or gap.

In addition, we’ve added support for Python 3.5 on the Mac, enhanced our .NET property support and added a number of useful new parameters.

We have also made a significant number of updates to the Gurobi Instant Cloud including:

• More intuitive interface — Get up and running even more quickly
• Enhanced Gurobi API support — Launch Instant Cloud instances directly from the Gurobi APIs (or through a license file) for easier integration into your applications
• Support for machine pools — Configure multiple machines as a single group, for easy launching and management