https://github.com/jump-dev/sdpa.jl
A Julia interface to the SDPA semidefinite programming solver
https://github.com/jump-dev/sdpa.jl
julia jump-jl semidefinite-programming
Last synced: 6 months ago
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A Julia interface to the SDPA semidefinite programming solver
- Host: GitHub
- URL: https://github.com/jump-dev/sdpa.jl
- Owner: jump-dev
- License: other
- Created: 2016-11-19T16:12:55.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2024-11-12T00:27:52.000Z (11 months ago)
- Last Synced: 2025-04-11T11:22:16.863Z (6 months ago)
- Topics: julia, jump-jl, semidefinite-programming
- Language: Julia
- Homepage: http://sdpa.sourceforge.net/
- Size: 185 KB
- Stars: 11
- Watchers: 3
- Forks: 4
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# SDPA.jl
[](https://github.com/jump-dev/SDPA.jl/actions?query=workflow%3ACI)
[](https://codecov.io/gh/jump-dev/SDPA.jl)
[SDPA.jl](https://github.com/jump-dev/SDPA.jl) is a wrapper for the
[SDPA](http://sdpa.sourceforge.net/) semidefinite programming solver in double
precision floating point arithmetic.
## Affiliation
This wrapper is maintained by the JuMP community and is not a product of the
SDPA developers.
## License
`SDPA.jl` is licensed under the [MIT License](https://github.com/jump-dev/SDPA.jl/blob/master/LICENSE.md).
The underlying solver, [SDPA](http://sdpa.sourceforge.net/) is licensed
under the [GPL v2 license](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html).
## Installation
Install SDPA using `Pkg.add`:
```julia
import Pkg
Pkg.add("SDPA")
```
In addition to installing the SDPA.jl package, this will also download and
install the SDPA binaries. (You do not need to install SDPA separately.)
If you see an error similar to:
```julia
INFO: Precompiling module GZip.
ERROR: LoadError: LoadError: error compiling anonymous: could not load library "libz"
```
please see [GZip.jl#54](https://github.com/JuliaIO/GZip.jl/issues/54) or [Flux.jl#343](https://github.com/FluxML/Flux.jl/issues/343). In particular, in Ubuntu this issue may be resolved by running
```bash
sudo apt-get install zlib1g-dev
```
See [SDPAFamily](https://github.com/ericphanson/SDPAFamily.jl) for the other
solvers, SDPA-GMP, SDPA-DD, and SDPA-QD of the family.
## Use with JuMP
```julia
using JuMP, SDPA
model = Model(SDPA.Optimizer)
# Optionally set parameters, for example:
set_attribute(model, "Mode", SDPA.PARAMETER_DEFAULT)
```
## MathOptInterface API
The SDPA optimizer supports the following constraints and attributes.
List of supported objective functions:
* [`MOI.ObjectiveFunction{MOI.ScalarAffineFunction{Float64}}`](@ref)
List of supported variable types:
* [`MOI.Nonnegatives`](@ref)
* [`MOI.PositiveSemidefiniteConeTriangle`](@ref)
List of supported constraint types:
* [`MOI.ScalarAffineFunction{Float64}`](@ref) in [`MOI.EqualTo{Float64}`](@ref)
List of supported model attributes:
* [`MOI.ObjectiveSense()`](@ref)
## Options
SDPA has three modes that give default value to all ten parameters.
The following table gives the default values for each parameter and mode.
| Parameter | `PARAMETER_DEFAULT` | `PARAMETER_UNSTABLE_BUT_FAST` | `PARAMETER_STABLE_BUT_SLOW` |
| ------------ | ------- | ------ | ------ |
| MaxIteration | 100 | 100 | 1000 |
| EpsilonStar | 1.0e-7 | 1.0e-7 | 1.0e-7 |
| LambdaStar | 1.0e+2 | 1.0e+2 | 1.0e+4 |
| OmegaStar | 2.0 | 2.0 | 2.0 |
| LowerBound | 1.0e+5 | 1.0e+5 | 1.0e+5 |
| UpperBound | 1.0e+5 | 1.0e+5 | 1.0e+5 |
| BetaStar | 0.1 | 0.01 | 0.1 |
| BetaBar | 0.2 | 0.02 | 0.3 |
| GammaStar | 0.9 | 0.95 | 0.8 |
| EpsilonDash | 1.0e-7 | 1.0e-7 | 1.0e-7 |
By default, we put SDPA in the `SDPA.PARAMETER_DEFAULT` mode.
Change the mode using the `"Mode"` option:
```julia
using JuMP, SDPA
model = Model(SDPA.Optimizer)
set_attribute(model, "Mode", SDPA.PARAMETER_STABLE_BUT_SLOW)
```
Note that the parameters are set in the order they are given, so you can set
a mode and then modify parameters from this mode.
```julia
using JuMP, SDPA
model = Model(SDPA.Optimizer)
set_attribute(model, "Mode", SDPA.PARAMETER_STABLE_BUT_SLOW)
set_attribute(model, "MaxIteration", 100)
```
The choice of parameter mode has a large impact on the performance and stability
of SDPA, and not necessarily in the way implied by the names of the modes; for
example, `PARAMETER_UNSTABLE_BUT_FAST` can be more stable than the other modes
for some problems. You should try each mode to see how it performs on your
specific problem. See [SDPA.jl#17](https://github.com/jump-dev/SDPA.jl/issues/17)
for more details.