MOProblems.jl is a curated Julia library of benchmark problems for multiobjective optimization. It provides source-traceable problem implementations, a consistent evaluation API, registered analytical derivatives, and metadata-based catalog queries.
import Pkg
Pkg.add(url = "https://github.com/VectorOptimizationGroup/MOProblems.jl")See the installation guide for project environments and local checkouts.
using MOProblems
prob = DTLZ2()
x = rand(prob.nvar)
values = eval_f(prob, x)
J = eval_jacobian(prob, x)
names = filter_problems(has_jacobian = true)The MOProblems.jl documentation
contains the quick start, task-oriented guides, mathematical formulations,
API reference, and bibliography. Instructions for building it locally are in
docs/README.md.
- Curated, source-traceable benchmark implementations.
- Allocating and in-place APIs for objectives and registered derivatives.
- Catalog filters for dimensions, bounds, constraints, and derivative support.
- Per-family formulations, metadata, usage examples, and references.
Contributions are welcome! Please feel free to submit a Pull Request or open an Issue to discuss improvements or report bugs.