EvoOpt - Evolutionary Optimization in Python

EvoOpt: Evolutionary Optimization in Python

Python implementation of state-of-art meta-heuristic and evolutionary optimisation algorithms.

This library is implemented in Numpy (which was written in C) for fast processing speed

Table of Contents

• About the Project
  • Current support for algorithms
• Getting Started
  • Dependencies
  • Installation
• Usage
• Contributing
• License
• Contact
• Acknowledgements

About The Project

Current support for algorithms

[x] Genetic Algorithm

[x] Duelist Algorithm

[X] Particle Swarm Optimization

[X] Gravitational Search Algorithm

[X] Firefly Algorithm

[X] Simulated Annealing

[ ] Multi-Verse Optimization

[ ] Grey-Wolf Optimization

More algorithms to come...

Getting Started

There are four simple steps to run an optimization problem using EvoOpt

(Example 2 from example folder)

Prerequisites

from solver.DuelistAlgorithm import DuelistAlgorithm

**1. Define your function. Say you want to minimize the equation f=(x1,x2) = (x1)^2+(x2)^2 **

def f(x1,x2):
	return x1*x1+x2*x2

**2. Define the variables that can be manipulated for optimization. Define their names as string and put them in an array. **

x=["x1","x2"]

3. Define the boundaries for the manipulated variables:

Say:

x1 is bounded from -2 to 10 (-2 is min value of x1 and 10 is max value of x1)

x2 is bounded from 10 to 15 (10 is min value of x2 and 15 is max value of x2)

We can arrange these boundaries according to the definition array in step 2.

The corresponding code is:

 xmin=[-2,5]
 xmax=[10,15]

4. Setup the solver and start the solve procedure.

DA=DuelistAlgorithm(f,x,xmin,xmax,max_gen=1000)
DA.solve(plot=True)

Example Result

Dependencies

Numpy and Matplotlib

Windows:

$python -m pip install numpy matplotlib

Linux:

$pip install numpy matplotlib

Installation

You can use two methods for installation:

1. Install from github (recommended as this will download the newest version)

First download the git repository. You can do this by clicking the download button or using the git command:

$ git pull https://github.com/tsyet12/EvoOpt

$ cd (directory of EvoOpt)

$ pip install -e .

$ pip install EvoOpt

$python -m pip install EvoOpt