jmetalpy 0.5.1

JMetalPy. Python version of the jMetal framework

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<img src=docs/source/jmetalpy.png alt="jMetalPy">
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# jMetalPy: Python version of the jMetal framework
[](https://travis-ci.org/jMetal/jMetalPy)
[](https://readthedocs.org/projects/jmetalpy/)
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## Table of Contents
- [Installation](#installation)
- [Usage](#usage)
- [Features](#features)
- [License](#license)

## Installation
To download jMetalPy just clone the Git repository hosted in GitHub:
```bash
$ git clone https://github.com/jMetal/jMetalPy.git
$ python setup.py install
```

Alternatively, you can install it with `pip`:
```bash
$ pip install jmetalpy
```

## Usage
Examples of configuring and running all the included algorithms are located [in the docs](https://jmetalpy.readthedocs.io/en/latest/examples.html).

## Features
The current release of jMetalPy (v0.5.1) contains the following components:

* Algorithms: random search, NSGA-II, SMPSO, SMPSO/RP.
* Benchmark problems: ZDT1-6, DTLZ1-2, unconstrained (Kursawe, Fonseca, Schaffer, Viennet2), constrained (Srinivas, Tanaka).
* Encodings: real, binary.
* Operators: selection (binary tournament, ranking and crowding distance, random, nary random, best solution), crossover (single-point, SBX), mutation (bit-blip, polynomial, uniform, random).
* Quality indicators: hypervolume.
* Density estimator: crowding distance.
* Graphics: Pareto front plotting (2 or more objectives).
* Laboratory: Experiment class for performing studies.

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<img src=docs/source/visualization.png alt="Visualization">
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## License
This project is licensed under the terms of the MIT - see the [LICENSE](LICENSE) file for details.