Optimization.jl
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SciML
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...
It would be useful to have a good interface for recording the path of all evaluated `u`s and their fitness values. I have tried to make this happen, but it...
Using very small stepsize doesn't make sense since the point is to more effectively explore the parameter space
Is there a way that I could get the current iteration of the optimization inside of a callback. I would like to be able to access the number of times...
In the documentation for the solver [callback function](https://docs.sciml.ai/Optimization/stable/API/solve/#CommonSolve.solve-Tuple{OptimizationProblem,%20Any}), it simply states > The callback function callback is a function which is called after every optimizer step. Its signature is: >...
Hi. I am trying to minimize a sum of three terms for a parameter estimation problem where the magnitude of one of the terms is larger ( about an order...
https://arxiv.org/pdf/2302.00316.pdf
We should be able to work around it by using a closure. This will be done only after the derivatives have been defined in the `instantiate_function` such that only the...
When you type ?Optimization.solve you get a good overview of the arguments to solve. But the result of solve: res=Optimization.solve(...) Is not explained !! I have seen res.u and res.minimizer...
Example: ```julia import Optimization using Enzyme lookup_pg = Dict(5 => 11, 4 => 13, 2 => 15, 3 => 17, 1 => 19) ref_gen_idxs = [5, 4, 2, 3, 1]...
