Optimization functions for Julia
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Latest commit 11c935e Sep 26, 2016 @pkofod pkofod Refactor by introducing mutating update methods, and have optimize ac…
…t as a simple iteration manager.



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")