Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

OptimizationProblem type #24

Open
dpsanders opened this issue Feb 5, 2019 · 2 comments
Open

OptimizationProblem type #24

dpsanders opened this issue Feb 5, 2019 · 2 comments

Comments

@dpsanders
Copy link
Member

It would be useful to have an OptimizationProblem type that encodes the function and original box, dimension etc.

@ericphanson
Copy link
Contributor

Relatedly (and also kind of related to #44) I think it would be nice to have an OptimizationResults type that gets returned that would hold onto the problem data along with the results. What this would enable is you could call results = optimise(f, X) and then e.g. optimise(results, tol = ...) to tighten the tolerance without needing to repeat the work you already did; it can just keep subdividing from where it left off. This would be useful in conjunction with things like #44 so you can terminate after X number of function evaluations, check on the results, and decide to resume if you want to.

It could also hold statistics such as number of iterations, and perhaps a log of the min values (so you can see how fast it decreases; this could be enabled by keyword argument like it is in BlackBoxOptim). I think you could also support destructuring so that min_value, minimizers = optimize(f,X) still works as expected. And it could have a show method that formats the results nicely.

@dpsanders
Copy link
Member Author

Sounds like a great idea!

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants