Minimizing the 2D Rastrigin Function

This repository contains Python code for minimizing the 2D Rastrigin function, a well-known benchmark problem in optimization. The Rastrigin function is a non-convex function often used to evaluate the performance of optimization algorithms due to its complex, multimodal surface.

Overview

The Rastrigin function is defined as:

$f(x, y) = A \cdot 2 + (x^2 - A \cdot \cos(2 \pi x)) + (y^2 - A \cdot \cos(2 \pi y)),$

where A = 10.

The global minimum is at (x, y) = (0, 0), with f(0, 0) = 0.

Here, we used a MetaHeuristic Algorithm, and more particularly : Simulated Annealing.