Metadata-Version: 1.1
Name: metaheuristic-algorithms-python
Version: 0.1.1
Summary: Various metaheuristic algorithms implemented in Python
Home-page: https://github.com/tadatoshi/metaheuristic_algorithms_python
Author: Tadatoshi Takahashi
Author-email: tadatoshi@gmail.com
License: MIT
Description: # MetaheuristicAlgorithmsPython
        
        Various metaheuristic algorithms implemented in Python.
        
        This is equivalent to MetaheuristicAlgorithms written in Ruby (https://github.com/tadatoshi/metaheuristic_algorithms). The reason why I wrote it in Python is that I would like to potentially utilize Python's Scientific Computing libraries. 
        
        As a programming lanugage, I prefer Ruby, because it's fully Object-Oriented programming language (also Dynamic language) and because it has a community with the culture of writing unit tests. Both of these characteristics lead to cleaner, well structured, easy-to-maintain codes. Also it's easier to understand the other people's codes written in such a way. 
        
        But scientists use Python for their activities such as Scientific Computing, Optimization, Data Science, Data Mining, Machine Learning etc. In other words, Python has a community of scientists.  
        
        ## Installation
        
        Use ``pip3``:
        
        ```
        pip3 install metaheuristic_algorithms_python
        ```
        
        ## Supported Platforms
        
        * Python 3.4. 
        
        It's not tested on Python 2.6 or 2.7 yet. 
        
        ## Available Algorithms
        
        * Harmony Search
        
        ## Usage
        
        
        
        ## Development
        
        
        
        ## Contributing
        
        Bug reports and pull requests are welcome on GitHub at https://github.com/tadatoshi/metaheuristic_algorithms_python. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](contributor-covenant.org) code of conduct.
        
        
        ## License
        
        The project is available as open source under the terms of the [MIT License](http://opensource.org/licenses/MIT).
        
        
Keywords: control optimization engineering
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.4
