Gurobi Optimizer
Breakthrough New Capability
Find globally optimal solutions to classic bilinear pooling and blending problems.
- Non-Convex Quadratic Optimization – We added a new bilinear solver that allows you to solve problems with non-convex quadratic constraints and objectives.
Faster Than Ever
Our maniacal focus on speed continues.
Gurobi Version 9.0 delivers significant performance improvements across LP, MIP, and MIQP problem types compared to v8.1.
- LP – In default settings is 7% faster.
- Barrier – 7% faster and an additional 4% faster with computers supporting AVX 512.
- MIP – 18% faster overall and 26% faster on difficult models that take more than 100 seconds to solve.
- MIQP – 24% faster.
We are happy to help you benchmark your models with Gurobi v9.0. Please submit a Gurobi support ticket to get started.
Ease of Use
New functionality in the Optimizer simplifies your workflow.
- Python Matrix API – We have extended our Python interface to support matrix-oriented modeling using NumPy or SciPy matrices.
- Piecewise-Linear (PWL) Constraints – You can now add PWL constraints directly as a modeling construct instead of having to represent them as a combination of linear and SOS constraints.
- Function Constraints With Automatic PWL Translation – This release allows you to add nine basic, nonlinear, univariate function constraints, including polynomial, exponential, logarithmic, and trigonometric functions. We will perform an automatic piecewise-linear approximation of these functions.
- MIP Scenario Analysis – This new feature allows you to describe multiple sets of changes to a model (scenarios) and computes the impact of these changes on the solution.
- New Solution Improvement Heuristic – New, much more effective heuristic for focusing on improving MIP solutions.
- Intermediate Solution Files – We now allow you to write solutions found during the MIP solution process to files as soon as they are discovered.
