Gurobi is a powerful commercial suite of optimization products, which includes simplex and parallel barrier solvers to handle linear programming (LP) and quadratic progermming (QP), also quadratically constrained (QCP) and the mixed-integer variations thereof (MIP, MIQP, MIQCP). It also supports some types of general constraints. The framework used by the drivers supports automatic reformulation for many expression types; the relative guide can be found here.

[Read More] [Options] [Download]


Our enhanced Gurobi driver (previously know as x-gurobi) is now the default Gurobi driver. The new driver provides significantly extended modeling support for logical and nonlinear operators natively through Gurobi’s built-in “general constraints” and through linearizations performed by the MP library. There are two binaries in this package: gurobi [options] is the new version, gurobiasl [options] is the legacy version. If you are upgrading an existing installation and encounter any issues with the new version please report them to

How to use it

ampl: option solver gurobi; # change the solver
ampl: option gurobi_options 'option1=value1 option2=value2'; # specify options
ampl: solve; # solve the problem

At a glance



Solver options

Full list of solver options:

Many solver parameters can be changed directly from AMPL, by specifying them as a space separated string in the option gurobi_options. A list of all supported options is available here or can be obtained by executing the solver driver with the -= command line parameter:

gurobi -=

or from AMPL:

shell "gurobi -=";

Solver options can have multiple aliases, to accomodate for different user types. The main numenclature is given first in the -= output, then followed by aliases in brackets, see for example the listing for lim:iter:

lim:iter (iterlim, iterlimit)
      Iteration limit (default: no limit).

The main numenclature contains a prefix (lim: in this case) to help categorize and find the options relevant to a context. To list only the options with a specific prefix (lim: for this example), run:

gurobi -=lim:

Specifying solver options and solving a model

After formulating the model in AMPL, execute the following to select gurobi as solver and pass the two options: return_mipgap=3 and outlev=1.

option solver gurobi;
option gurobi_options "retmipgap=3 outlev=1";

Retrieving solutions

The outcome of the last optimization is stored in the AMPL parameter solve_result_num and the relative message in solve_result.

display solve_result_num, solve_result;

Handling infeasibility


When a model is unfeasible, one usedful information is finding the irreducible inconsistent sets, which are subsets of constraints that are incompatible. This is supported by the framework, see the description here.

Feasibility Relaxation

Another approach to tackle infeasibilities is to use feasibility relaxation to find a solution which only penalizes infeasibilities. This is supported via the framework, see the description here.

Gurobi compute server and Gurobi cloud

Gurobi supports solving your model on other machines in two alternative ways:

  • Compute server - where a computer (or a cluster) can be configured to the specific task of solving models via gurobi

  • Gurobi cloud - where the compute server is by Gurobi itself

To use a compute server, the option tech:server must be set, together with appropriate values for the tech:server_* options. For gurobi instant cloud, the options tech:cloudid and tech:cloudkey must be set, and optionally the other options tech:cloud*, for example:

# Solve with compute server
option gurobi_options "tech:server=";

# Solve with gurobi instant cloud
option gurobi_options "tech:cloudid=mygurobiid tech:cloudkey=myprivatekey";