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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 inte...

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Here's an MWE where the callback function is ignored for the `CMAEvolutionStrategyOpt` solver: ``` using GalacticOptim using GalacticCMAEvolutionStrategy rosenbrock(x,p) = (p[1] - x[1])^2 + p[2] * (x[2] - x[1]^2)^2 x0...

The example from the documentation throws an error. ```julia julia> using GalacticOptim, Nonconvex julia> Nonconvex.@load Ipopt [ Info: Attempting to load the package NonconvexIpopt. [ Info: Loading succesful. julia> rosenbrock(x,...

Correct me if I am wrong, but it is not very clear in the documentation how would one go about defining constraints that are **not** "box" constraints. One of the...

Providing the `cb` keyword argument to a `GalacticOptim.solve` call that uses an optimizer from the `Metaheuristics.jl` package currently yields the warning 'Callback argument is currently not used by Metaheuristics.AbstractAlgorithm' and...

Hello! I have the following code I have been tirelessly revising but I cannot manage to make it work. How can I solve the following error? ``` ERROR: LoadError: MethodError:...

Hello, I am facing weird behavior. I created an optimization problem using the CMAEvolutionStrategy and the solution converges well however the solution returned by the solve function does not make...

See http://www.juliaopt.org/MathOptInterface.jl/dev/apireference/#MathOptInterface.ObjectiveSense The default should be `min_sense` and you might even want to only implement that in the first iteration, but you want to do the API for this correctly...

See https://github.com/SciML/GalacticOptim.jl/issues/130 as well.

Would it be possible to combine the evaluation of the gradient and the functional in a single function? It seems that currently, the [`OptimizationFunction`](https://galacticoptim.sciml.ai/stable/API/optimization_function/) is designed to evaluate `f` and...