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GLPK.jl is a wrapper for the GNU Linear Programming Kit library.
It has two components:
- a thin wrapper around the complete C API
- an interface to MathOptInterface
The C API can be accessed via GLPK.glp_XXX functions, where the names and
arguments are identical to the C API. See the /tests folder for inspiration.
The package is registered in the General registry
and so can be installed with Pkg.add.
julia> import Pkg
julia> Pkg.add("GLPK")In addition to installing the GLPK.jl package, this will also download and install the GLPK binaries. (You do not need to install GLPK separately.) If you require a custom build of GLPK, see the "Custom Installation" instructions below.
To install custom built GLPK binaries set the environmental variable
JULIA_GLPK_LIBRARY_PATH and call import Pkg; Pkg.build("GLPK"). For example,
if the libraries are installed in /opt/lib just call:
ENV["JULIA_GLPK_LIBRARY_PATH"] = "/opt/lib"
Pkg.build("GLPK")If you do not want BinaryProvider to download the default binaries on install
set JULIA_GLPK_LIBRARY_PATH before calling import Pkg; Pkg.add("GLPK").
To switch back to the default binaries clear JULIA_GLPK_LIBRARY_PATH and call
import Pkg; Pkg.build("GLPK").
Use GLPK.Optimizer to create a new optimizer object for use with
MathOptInterface or JuMP.
In the following examples the time limit is set to one minute and logging is turned off.
using GLPK
model = GLPK.Optimizer()
MOI.set(model, MOI.RawParameter("tm_lim"), 60_000) # tm_lim is in milliseconds.
MOI.set(model, MOI.RawParameter("msg_lev"), GLPK.GLP_MSG_OFF)For JuMP, use:
using JuMP, GLPK
model = Model(GLPK.Optimizer)
set_optimizer_attribute(model, "tm_lim", 60 * 1_000)
set_optimizer_attribute(model, "msg_lev", GLPK.GLP_MSG_OFF)