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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.

Home Page: https://docs.sciml.ai/Optimization/stable/

License: MIT License

Julia 100.00%
optimization local-optimization global-optimization automatic-differentiation algorithmic-differentiation sciml scientific-machine-learning hacktoberfest julia mixed-integer-programming

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