The goal is to utilize a form of evolutionary learning, a genetic algorithm, to find the minima of a function given certain constraints. The function to be optimized is the 2-variable Goldstein-Price function.
Genetic algorithms can effectively be used to find the maxima/minima of a function, by searching the function variable space to find the global optimum. The particular function to optimize in this test is the Goldstein-Price function, you can google the equation.
The function is subject to the following constraints: −2.0 ≤ x ≤ 2.0, −2.0 ≤ y ≤ 2.0. Below is a visualization of the function in the defined range. Note the presence of several local minima, and one global minimum.
We will try to find the global minimum of the mentioned function.