Evolutionary Algorithm Optimizer

A simple evolutionary algorithm implementation for function optimization.

Overview

This project implements an evolutionary algorithm to optimize two different multi-modal functions:

Function 1: Modified Sine Function

$f(x_1,x_2) = 3-\sin^2(jx_1)-\sin^2(jx_2)$

where:

$x_1,x_2 \in [0,6]$
For $j=2,3,4,5$, the function has 16, 36, 64, and 100 global optima respectively
Current implementation uses $j=2$

Function 2: Shubert Function

$f(x_1,...,x_n) = \prod_{i=1}^{n}\sum_{j=1}^{5}j\cos[(j+1)x_i+j]$

where:

$x_i \in [-10,10]$
For $n=2$, the function has 18 different global optima

Features

Population initialization
Custom selection mechanism
Crossover operation (rate: 0.4)
Mutation operation (rate: 0.1)
Real-time 3D visualization

Requirements

python
numpy==1.21.0
pandas==2.0.0
matplotlib==3.5.0