SciML/Optimization.jl

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.

Juliaoptimizationjuliaautomatic-differentiationglobal-optimizationhacktoberfestnonlinear-optimizationconvex-optimizationalgorithmic-differentiationmixed-integer-programmingscientific-machine-learningderivative-free-optimizationscimllocal-optimization
This is stars and forks stats for /SciML/Optimization.jl repository. As of 02 May, 2024 this repository has 570 stars and 66 forks.

Optimization.jl Optimization.jl is a package with a scope that is beyond your normal global optimization package. Optimization.jl seeks to bring together all of the optimization packages it can find, local and global, into one unified Julia interface. This means, you learn one package and you learn them all! Optimization.jl adds a few high-level features, such as integrating with automatic differentiation, to make its usage fairly simple for most cases, while allowing all of the options in a single unified...
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