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June 2016

SCIP.jl

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SCIP.jl is a Julia interface to the SCIP solver.

Affiliation

This wrapper is maintained by the SCIP project with the help of the JuMP community.

License

SCIP.jl is licensed under the MIT License.

The underlying solver, scipopt/scip, is licensed under the Apache 2.0 license.

Installation

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.

Custom installations

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 with JuMP

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)

Options

See the SCIP documentation for a list of supported options.

MathOptInterface API

The SCIP optimizer supports the following constraints and attributes.

List of supported objective functions:

List of supported variable types:

List of supported constraint types:

List of supported model attributes:

Design considerations

Wrapping the public API

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.

Memory management

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 nonlinear operators

Supported operators in nonlinear expressions are as follows:

  • +
  • -
  • *
  • /
  • ^
  • sqrt
  • exp
  • log
  • abs
  • cos
  • sin

Errors with nonlinear models

When solving a nonlinear model, you may encounter Error: no BLAS/LAPACK library loaded!, this comes from Ipopt, see the README on Ipopt.jl.