Enterprise Features &Even Better Performance
Gurobi Version 9.5

GUROBI 9.5

The world’s fastest solver justkeeps getting better. Gurobi
9.5 includes new enterprisefeatures, product enhancements,
and an even faster computeengine—with impressive
performance improvements acrossall supported problem types.

Learn more about ourlatest releaseEven Faster Performance

MIP

LP

Compared to the Gurobi 9.1 release, Gurobi 9.5 has boosted its speeds across the board.

PROBLEM TYPESOVERALL SPEED-UP

HARD MODELS• Concurrent

14%

54%

• Primal Simplex

23%

43%

• Dual Simplex

20%

43%

• Barrier

18%56%• MIP

15%27%• Convex MIQP

30%68%• Convex MIQCP

33%

78%

• Non-Convex MIQCP

3.0x

7.5x

(>1s)

(>100s)New Features and Enhancements
Customers will discover over a dozen enhancements across the product, such as powerful new heuristics
for non-convex quadratic models, norm constraints, deterministic work measures, memory limit parameters,
and more user control of IIS computation, as well as improvements to callbacks and tuning.

Gurobi Optimizer
NLP Heuristic for Non-Convex Quadratic
ModelsWe have added a non-linear barrier solver
for quickly finding feasible solutions tonon-convex quadratic models.

Memory Limit
The new MemLimit parameter allows
you to terminate optimization whenthe memory used by the optimization
exceeds the specified value.

Lazy Constraints in the NoRel Heuristic
Lazy constraints are now supported
in the NoRel heuristic. You will receive
solution callbacks and be given theopportunity to cut off those solutions
with lazy constraints.

New Cut Type - Lift-and-Project Cuts
This release includes a new cut
type: lift-and-project cuts. The
new LiftProjectCuts parameter provides
some control over the generation ofthese cuts.

New Callback for Exiting the NoRelHeuristic
The new Proceed callback method allows
you to smoothly transition from theNoRel heuristic to the MIP search.

New Simplex Warm Start Options
Several new options are available
for starting simplex from a previoussolution. Options are chosen using thenew LPWarmStart parameter.

Web License Service (WLS)
The new Web License Service enables
Gurobi on containerized environments(e.g., Docker, Kubernetes). Predefined
images are available on Docker Hub.

Writing Dualized Models
The new .DUA and .DLP file formats allow
you to write the dual formulation of an LP
problem.

Work Metric
We now include a deterministic workmeasure to enable exact reproducibilityof a solver run.

Norm General Constraint
Add norm constraints to your MIP model,
with support for 0-, 1-, 2-, and infinity
norms.

New Parameters and Attributes
In addition to the attributes andparameters directly tied to the newfeatures above, there are three additional
new attributes:
MaxVio: New attribute that gives
the maximum (unscaled) constraint
violation for the computed solution.
ConcurrentWinMethod: New attributethat indicates which algorithm
prevailed in a concurrent LP solve.
PoolIgnore: New attribute to selectvariables that should be ignored
when checking whether two solutions
differ in the solution pool.
IIS Force Flags
You now have more control over the
Irreducible Infeasible Subsystem (IIS)
algorithm. Specifically, you can indicatethat certain constraints or bounds should
be forced into the IIS, even if the resulting
subsystem is not minimal. Similarly, you
can exclude constraints or bounds fromthe IIS.
IIS Callbacks
New IIS callbacks allow you toprogrammatically track the progress ofthe IIS algorithm.

SOS Encoding Options
SOS constraints can now be formulated
in multiple different ways internally, which
can sometimes give better performance.
Tuning Tool Enhancements
We added a number of additional
controls to our tuning tool, including
control over termination and control over
how runtimes from multiple trials areaggregated.
Improvements in gurobipy
Type hints are now available for mostof the gurobipy classes and functions.
Moreover, indexing MVar and MConstr
objects is now more consistent withnumpy.
Universal2 Port for Mac
Supports both Apple silicon and Intel x64
processors.

Python SupportGurobi Optimizer 9.5 also showcases thecompany’s continued support for Python—Compute Server and Cluster Manager

the most popular programming language

Web License Service (WLS)
The new Web License Service alsoenables Gurobi Compute Server andCluster Manager to run on containerizedenvironments (e.g., Docker, Kubernetes).
Predefined images are available onDocker Hub.

interface and support for Python 3.10.

Integration with LDAP Repositories forCentralized User Management
LDAP support allows enterprise-grade
Compute Server deployments using anindustry-standard directory service foruser authentication and authorization.
Amazon Web Services DocumentDB 4.0
Database Support:
The Cluster Manager now supports
AWS DocumentDB 4.0 as a back-end
database. This expands your options
when deploying the Cluster Manager on
an AWS environment.

API Key Management
The Cluster Manager supports the ability
to disable/enable keys, set a description,and download and track API keys forimproved security.

in the world—with an improved Python

Account Management
The Cluster Manager now provides
system accounts, password policies,
read-only role usage and the ability todisable/enable accounts for improved
user management.
Usability
The Cluster Manager now provides
contextual help, settings management,permalinks, and job metrics for enhancedusability.

Even though the Gurobi Optimizer is the fastest mathematical optimizer in the world, we’re notgoing to rest on our laurels. We will keep pushing to improve and innovate because we’re passionate
about mathematical optimization and the difference it makes in solving real-world problems.
DR. TOBIAS ACHTERBERG

VP OF R&D, GUROBI OPTIMIZATIONSOLVE YOUR MOST COMPLEX CHALLENGES

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FREE FOR ACADEMIC USE
We make it easy for students, faculty, andresearchers to work with mathematicaloptimization. Whether for use in class or research,academics can use Gurobi Optimizer at no cost. All
the same Gurobi features and performance, withno limits on model size.

Our specialists are here to help you
succeed with mathematical optimization.
info@gurobi.com
www.gurobi.com