Provides a Julia wrapper for the PATH Solver for solving mixed complementarity problems
15 Stars
Updated Last
1 Year Ago
Started In
April 2016

PATHSolver.jl was completely re-written between v0.6 and v1.0. It now uses PATH v5.0 binaries, and integrates directly into JuMP. At this point, PATHSolver.jl only supports modeling linear problems. For nonlinear problems, use Complementarity.jl.

To revert to the old API, use:

import Pkg
Pkg.add(Pkg.PackageSpec(name = "PATHSolver", version = v"0.6.2"))

Then restart Julia for the change to take effect. The old documentation and source code is available on the path-solver-v0 branch.


A Julia interface to the PATH solver.

Build Status codecov


Install PATHSolver.jl as follows:

import Pkg; Pkg.add("PATHSolver")

By default, PATHSolver.jl will download a copy of the underlying PATH solver. To use a different version of PATH, see the Manual Installation section below.


Without a license, the PATH Solver can solve problem instances up to with up to 300 variables and 2000 non-zeros. For larger problems, this web page provides a temporary license that is valid for a year.

You can either store the license in the PATH_LICENSE_STRING environment variable, or you can use the PATHSolver.c_api_License_SetString function immediately after importing the PATHSolver package:

using PATHSolver
PATHSolver.c_api_License_SetString("<LICENSE STRING>")

where <LICENSE STRING> is replaced by the current license string.

Example usage

julia> using JuMP, PATHSolver

julia> M = [
           0  0 -1 -1
           0  0  1 -2
           1 -1  2 -2
           1  2 -2  4
4×4 Array{Int64,2}:
 0   0  -1  -1
 0   0   1  -2
 1  -1   2  -2
 1   2  -2   4

julia> q = [2, 2, -2, -6]
4-element Array{Int64,1}:

julia> model = Model(PATHSolver.Optimizer)
A JuMP Model
Feasibility problem with:
Variables: 0
Model mode: AUTOMATIC
CachingOptimizer state: EMPTY_OPTIMIZER
Solver name: Path 5.0.00

julia> set_optimizer_attribute(model, "output", "no")

julia> @variable(model, x[1:4] >= 0)
4-element Array{VariableRef,1}:

julia> @constraint(model, M * x .+ q ⟂ x)
[-x[3] - x[4] + 2, x[3] - 2 x[4] + 2, x[1] - x[2] + 2 x[3] - 2 x[4] - 2, x[1] + 2 x[2] - 2 x[3] + 4 x[4] - 6, x[1], x[2], x[3], x[4]]  MOI.Complements(4)

julia> optimize!(model)
Reading options file /var/folders/bg/dzq_hhvx1dxgy6gb5510pxj80000gn/T/tmpiSsCRO
Read of options file complete.

Path 5.0.00 (Mon Aug 19 10:57:18 2019)
Written by Todd Munson, Steven Dirkse, Youngdae Kim, and Michael Ferris

julia> value.(x)
4-element Array{Float64,1}:

julia> termination_status(model)
LOCALLY_SOLVED::TerminationStatusCode = 4

Factorization methods

By default, PATHSolver.jl will download the LUSOL shared library. To use LUSOL, set the following options:

model = Model(PATHSolver.Optimizer)
set_optimizer_attribute(model, "factorization_method", "blu_lusol")
set_optimizer_attribute(model, "factorization_library_name", PATHSolver.LUSOL_LIBRARY_PATH)

To use factorization_method umfpack you will need the umfpack shared lib that is available directly from the developers of that code for academic use.

Manual installation

By default PATHSolver.jl will download a copy of the libpath library. If you already have one installed and want to use that, set the PATH_JL_LOCATION environment variable to point to the libpath50.xx library, then run"PATHSolver").

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