Minimalist And Customizable Optimization Package
Project description
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
policies
folder to manage the way of update and use solution. - callbacks: callbacks folder where
Callback
class is available for making callback instructions 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 ?
Fully documentation of package with examples is available.
You can also see examples of use:
- in the knapsackExample.py python file for mono-objective.
- in the knapsackMultiExample.py python file for multi-objective.
Add as dependency
git submodule add https://github.com/jbuisine/macop.git
License
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