SCIP.jl is a Julia interface to the SCIP solver.
This wrapper is maintained by the SCIP project with the help of the JuMP community.
SCIP.jl
is licensed under the MIT License.
The underlying solver, scipopt/scip, is licensed under the Apache 2.0 license.
Install SCIP.jl using Pkg.add
:
import Pkg
Pkg.add("SCIP")
On MacOS and Linux, installing the SCIP Julia package will work out of the box
and install the SCIP_jll.jl
and
SCIP_PaPILO_jll.jl
dependencies.
On Windows, a separate installation of SCIP is still mandatory, as detailed in the "Custom installation" section below.
If you use an older Julia version, Windows, or you want a custom SCIP installation, you must manually install the SCIP binaries.
Once installed, set the SCIPOPTDIR
environment variable to point to the
installation path, that is, depending on your operating system,
$SCIPOPTDIR/lib/libscip.so
, $SCIPOPTDIR/lib/libscip.dylib
, or
$SCIPOPTDIR/bin/scip.dll
must exist.
Then, install SCIP.jl
using Pkg.add
and Pkg.build
:
ENV["SCIPOPTDIR"] = "/Users/Oscar/code/SCIP"
import Pkg
Pkg.add("SCIP")
Pkg.build("SCIP")
Use SCIP with JuMP as follows:
using JuMP, SCIP
model = Model(SCIP.Optimizer)
set_attribute(model, "display/verblevel", 0)
set_attribute(model, "limits/gap", 0.05)
See the SCIP documentation for a list of supported options.
The SCIP optimizer supports the following constraints and attributes.
List of supported objective functions:
List of supported variable types:
List of supported constraint types:
MOI.ScalarAffineFunction{Float64}
inMOI.EqualTo{Float64}
MOI.ScalarAffineFunction{Float64}
inMOI.GreaterThan{Float64}
MOI.ScalarAffineFunction{Float64}
inMOI.Interval{Float64}
MOI.ScalarAffineFunction{Float64}
inMOI.LessThan{Float64}
MOI.ScalarQuadraticFunction{Float64}
inMOI.EqualTo{Float64}
MOI.ScalarQuadraticFunction{Float64}
inMOI.GreaterThan{Float64}
MOI.ScalarQuadraticFunction{Float64}
inMOI.Interval{Float64}
MOI.ScalarQuadraticFunction{Float64}
inMOI.LessThan{Float64}
MOI.VariableIndex
inMOI.EqualTo{Float64}
MOI.VariableIndex
inMOI.GreaterThan{Float64}
MOI.VariableIndex
inMOI.Integer
MOI.VariableIndex
inMOI.Interval{Float64}
MOI.VariableIndex
inMOI.LessThan{Float64}
MOI.VariableIndex
inMOI.ZeroOne
MOI.VectorOfVariables
inMOI.SOS1{Float64}
MOI.VectorOfVariables
inMOI.SOS2{Float64}
List of supported model attributes:
All of the public API methods are wrapped and available within the SCIP
package. This includes the scip_*.h
and pub_*.h
headers that are collected
in scip.h
, as well as all default constraint handlers (cons_*.h
.)
The wrapped functions do not transform any data structures and work on the raw
pointers (for example, SCIP*
in C, Ptr{SCIP_}
in Julia). Convenience wrapper
functions based on Julia types are added as needed.
Programming with SCIP requires dealing with variable and constraint objects that use reference counting for memory management.
The SCIP.Optimizer
wrapper type collects lists of SCIP_VAR*
and SCIP_CONS*
under the hood, and it releases all references when it is garbage collected
itself (via finalize
).
When adding a variable (add_variable
) or a constraint (add_linear_constraint
),
an integer index is returned. This index can be used to retrieve the SCIP_VAR*
or SCIP_CONS*
pointer via get_var
and get_cons
respectively.
Supported operators in nonlinear expressions are as follows:
+
-
*
/
^
sqrt
exp
log
abs
cos
sin