Univariate and multivariate optimization in Julia.
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Optim.jl is a package for univariate and multivariate optimization of functions. A typical example of the usage of Optim.jl is
using Optim
rosenbrock(x) = (1.0 - x[1])^2 + 100.0 * (x[2] - x[1]^2)^2
result = optimize(rosenbrock, zeros(2), BFGS())Which gives the output
Results of Optimization Algorithm
* Algorithm: BFGS
* Starting Point: [0.0,0.0]
* Minimizer: [0.9999999929485311,0.9999999859278653]
* Minimum: 4.981810e-17
* Iterations: 21
* Convergence: true
* |x - x'| < 1.0e-32: false
* |f(x) - f(x')| / |f(x)| < 1.0e-32: true
* |g(x)| < 1.0e-08: false
* Reached Maximum Number of Iterations: false
* Objective Function Calls: 157
* Gradient Calls: 157
For more details and options, see the documentation (stable | latest).
The package is registered in METADATA.jl and can be installed with Pkg.add.
julia> Pkg.add("Optim")