Optimisation modules built for optimization problem during thesis
Jérôme BUISINE
26a13018f4
UCB policy implemented
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| macop | 3 lat temu | |
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| README.md | 3 lat temu | |
| __init__.py | 4 lat temu | |
| build.sh | 3 lat temu | |
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| mainExample.py | 3 lat temu | |
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| setup.py | 3 lat temu |
README.md
Minimalist And Customizable Optimization Package
Description
macop is an optimization Python package which not implement the whole available algorithms in the literature but let you the possibility to quickly develop and test your own algorithm and strategies. The main objective of this package is to be the most flexible as possible and hence, to offer a maximum of implementation possibilities.
Modules
- algorithms: generic and implemented OR algorithms
- evaluator: example of an evaluation function to use (you have to implement your own evaluation function)
- solutions: solutions used to represent problem data
- operators: mutators, crossovers update of solution. This folder also has
policiesfolder to manage the way of update and use solution. - checkpoints: checkpoints folder where
Checkpointclass is available for making checkpoint every number of evaluations.
Note: you can pass a custom validator function to the algorithm in order to check is solution is always correct for your needs after an update.
How to use ?
You can see an example of use in the mainExample.py python file.
Fully documentation of package with examples is also available.
Add as dependency
git submodule add https://github.com/jbuisine/macop.git