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juliahub.com : OptimizationFlux
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
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Source
- Homepage
- Documentation
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purl: pkg:julia/OptimizationFlux
Keywords: hacktoberfest, global-optimization, julia, mixed-integer-programming, nonlinear-optimization, convex-optimization, derivative-free-optimization, local-optimization, optimization, algorithmic-differentiation, automatic-differentiation, sciml, scientific-machine-learning
License: MIT
Latest release: over 3 years ago
First release: over 1 year ago
Dependent packages: 2
Stars: 655 on GitHub
Forks: 71 on GitHub
Total Commits: 1255
Committers: 63
Average commits per author: 19.921
Development Distribution Score (DDS): 0.579
More commit stats: commits.ecosyste.ms
See more repository details: repos.ecosyste.ms
Funding links: https://github.com/sponsors/SciML
Last synced: 1 day ago