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MOProblems.jl

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.

Installation

import Pkg
Pkg.add(url = "https://github.com/VectorOptimizationGroup/MOProblems.jl")

See the installation guide for project environments and local checkouts.

Quick Example

using MOProblems

prob = DTLZ2()
x = rand(prob.nvar)

values = eval_f(prob, x)
J = eval_jacobian(prob, x)

names = filter_problems(has_jacobian = true)

Documentation

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.

Highlights

  • 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.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request or open an Issue to discuss improvements or report bugs.