https://github.com/jump-dev/xpress.jl
A Julia interface to the FICO Xpress Optimization suite
https://github.com/jump-dev/xpress.jl
julia jump-jl linear-programming mixed-integer-programming nonlinear-programming
Last synced: 18 days ago
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A Julia interface to the FICO Xpress Optimization suite
- Host: GitHub
- URL: https://github.com/jump-dev/xpress.jl
- Owner: jump-dev
- Created: 2016-02-27T20:25:52.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2025-04-04T02:42:42.000Z (26 days ago)
- Last Synced: 2025-04-11T11:55:11.860Z (19 days ago)
- Topics: julia, jump-jl, linear-programming, mixed-integer-programming, nonlinear-programming
- Language: Julia
- Homepage: https://www.fico.com/en/products/fico-xpress-optimization
- Size: 1.11 MB
- Stars: 66
- Watchers: 4
- Forks: 31
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Xpress.jl
[](https://github.com/jump-dev/Xpress.jl/actions?query=workflow%3ACI)
[](https://codecov.io/gh/jump-dev/Xpress.jl)
[Xpress.jl](https://github.com/jump-dev/Xpress.jl) is a wrapper for the [FICO Xpress Solver](https://www.fico.com/products/fico-xpress-solver).
It has two components:
- a thin wrapper around the complete C API
- an interface to [MathOptInterface](https://github.com/jump-dev/MathOptInterface.jl)
## Affiliation
The Xpress wrapper for Julia is community driven and not officially supported
by FICO Xpress. If you are a commercial customer interested in official support
for Julia from FICO Xpress, let them know.
## Getting help
If you need help, please ask a question on the [JuMP community forum](https://jump.dev/forum).
If you have a reproducible example of a bug, please [open a GitHub issue](https://github.com/jump-dev/Xpress.jl/issues/new).
## License
`Xpress.jl` is licensed under the [MIT License](https://github.com/jump-dev/Xpress.jl/blob/master/LICENSE.md).
The underlying solver is a closed-source commercial product for which you must
[purchase a license](https://www.fico.com/products/fico-xpress-solver).
## Installation
First, obtain a license of Xpress and install Xpress solver, following the
[instructions on the FICO website](https://www.fico.com/products/fico-xpress-solver).
Ensure that the `XPRESSDIR` license variable is set to the install location by
checking the output of:
```julia
julia> ENV["XPRESSDIR"]
```
Then, install this package using:
```julia
import Pkg
Pkg.add("Xpress")
```
If you encounter an error, make sure that the `XPRESSDIR` environmental variable
is set to the path of the Xpress directory. This should be part of a standard
installation. The Xpress library will be searched for in `XPRESSDIR/lib` on Unix
platforms and `XPRESSDIR/bin` on Windows.
For example, on macOS, you may need:
```julia
ENV["XPRESSDIR"] = "/Applications/FICO Xpress/xpressmp/"
import Pkg
Pkg.add("Xpress")
```
### Skipping installation
By default, building Xpress.jl will fail if the Xpress library is not found.
This may not be desirable in certain cases, for example when part of a package's
test suite uses Xpress as an optional test dependency, but Xpress cannot be
installed on a CI server running the test suite.
To skip the error, set the `XPRESS_JL_SKIP_LIB_CHECK` environment variable to
`true` to make Xpress.jl installable (but not usable).
```julia
ENV["XPRESS_JL_SKIP_LIB_CHECK"] = true
import Pkg
Pkg.add("Xpress")
```
## Use with Xpress_jll
Instead of manually installing Xpress, you can use the binaries provided by the
[Xpress_jll.jl](https://github.com/jump-dev/Xpress_jll.jl) package.
By using Xpress_jll, you agree to certain license conditions. See the
[Xpress_jll.jl README](https://github.com/jump-dev/Xpress_jll.jl/tree/master?tab=readme-ov-file#license)
for more details.
```julia
import Xpress_jll
# This environment variable must be set _before_ loading Xpress.jl
ENV["XPRESS_JL_LIBRARY"] = Xpress_jll.libxprs
# Point to your xpauth.xpr license file
ENV["XPAUTH_PATH"] = "/path/to/xpauth.xpr"
using Xpress
```
If you plan to use Xpress_jll, `Pkg.add("Xpress")` will fail because it cannot
find a local installation of Xpress. Therefore, you should set
`XPRESS_JL_SKIP_LIB_CHECK` before installing.
To add a specific version of Xpress with `Xpress_jll` do:
```julia
import Pkg
Pkg.add(name = "Xpress_jll", rev = "v8.14.0")
```
If the version is not found, please open and issue at https://github.com/jump-dev/Xpress_jll.jl
## Use with JuMP
To use Xpress with JuMP, use:
```julia
using JuMP, Xpress
model = Model(Xpress.Optimizer)
# Modify options, for example:
set_attribute(model, "PRESOLVE", 0)
```
## Options
For other parameters see the [Xpress Optimizer manual](https://www.fico.com/fico-xpress-optimization/docs/latest/solver/optimizer/HTML/).
If `logfile` is set to `""`, the log file is disabled and output is printed to
the console ([there might be issues with console output on windows (it is manually implemented with callbacks)](https://www.fico.com/fico-xpress-optimization/docs/latest/solver/optimizer/HTML/OUTPUTLOG.html)).
If `logfile` is set to a file's path, output is printed to that file. By
default, `logfile = ""` (console).
### Custom options
* `MOI_POST_SOLVE::Bool`: set this attribute to `false` to skip `XPRSpostsolve`.
This is most useful in older versions of Xpress that throw an error if the
model is infeasible.
* `MOI_IGNORE_START::Bool`: set this attribute to `true` to skip setting
`MOI.VariablePrimalStart`
* `MOI_WARNINGS::Bool`: set this attribute to `false` to turn off the various
warnings printed by the MathOptInterface wrapper
* `MOI_SOLVE_MODE::String`: set the `flags` argument to
[`lpoptimize`](https://www.fico.com/fico-xpress-optimization/docs/latest/solver/optimizer/R/HTML/lpoptimize.html)
* `XPRESS_WARNING_WINDOWS::Bool`: set this attribute to `false` to turn of
warnings on Windows.
## Callbacks
Here is an example using Xpress's solver-specific callbacks.
```julia
using JuMP, Xpress, Test
model = direct_model(Xpress.Optimizer())
@variable(model, 0 <= x <= 2.5, Int)
@variable(model, 0 <= y <= 2.5, Int)
@objective(model, Max, y)
function my_callback_function(cb_data)
prob = cb_data.model
p_value = Ref{Cint}(0)
ret = Xpress.Lib.XPRSgetintattrib(prob, Xpress.Lib.XPRS_MIPINFEAS, p_value)
if p_value[] > 0
return # There are integer infeasibilities. The solution is fractional.
end
p_obj, p_bound = Ref{Cdouble}(), Ref{Cdouble}()
Xpress.Lib.XPRSgetdblattrib(prob, Xpress.Lib.XPRS_MIPBESTOBJVAL, p_obj)
Xpress.Lib.XPRSgetdblattrib(prob, Xpress.Lib.XPRS_BESTBOUND, p_bound)
rel_gap = abs((p_obj[] - p_bound[]) / p_obj[])
@info "Relative gap = $rel_gap"
# Before querying `callback_value`, you must call:
Xpress.get_cb_solution(unsafe_backend(model), cb_data.model)
x_val = callback_value(cb_data, x)
y_val = callback_value(cb_data, y)
# You can submit solver-independent MathOptInterface attributes such as
# lazy constraints, user-cuts, and heuristic solutions.
if y_val - x_val > 1 + 1e-6
con = @build_constraint(y - x <= 1)
MOI.submit(model, MOI.LazyConstraint(cb_data), con)
elseif y_val + x_val > 3 + 1e-6
con = @build_constraint(y + x <= 3)
MOI.submit(model, MOI.LazyConstraint(cb_data), con)
end
if rand() < 0.1
# You can terminate the callback as follows:
Xpress.Lib.XPRSinterrupt(cb_data.model, 1234)
end
return
end
set_attribute(model, Xpress.CallbackFunction(), my_callback_function)
set_attribute(model, "HEUREMPHASIS", 0)
optimize!(model)
@test termination_status(model) == MOI.OPTIMAL
@test primal_status(model) == MOI.FEASIBLE_POINT
@test value(x) == 1
@test value(y) == 2
```
## Environment variables
- `XPRESS_JL_SKIP_LIB_CHECK`: Used to skip build lib check as previously
described.
- `XPRESS_JL_NO_INFO`: Disable license info log.
- `XPRESS_JL_NO_DEPS_ERROR`: Disable error when do deps.jl file is found.
- `XPRESS_JL_NO_AUTO_INIT`: Disable automatic run of `Xpress.initialize()`.
Specially useful for explicitly loading the dynamic library.
- `XPRESS_JL_LIBRARY`: Provide a custom path to `libxprs`
- `XPAUTH_PATH`: Provide a custom path to the license file
## C API
The C API can be accessed via `Xpress.Lib.XPRSxx` functions, where the names and
arguments are identical to the C API.
See the [Xpress documentation](https://www.fico.com/fico-xpress-optimization/docs/latest/solver/optimizer/HTML)
for details.
## Documentation
For more information, consult the
[FICO optimizer manual](https://www.fico.com/fico-xpress-optimization/docs/latest/solver/optimizer/HTML).