What are Evolutionary Algorithms?

Developed by evolutionary scientists in the 1950s and 1960s, evolutionary algorithms draw inspiration from the adaptive processes found in natural evolution. These algorithms incorporate principles like natural selection, mutation, and recombination to tackle computational challenges that require the identification of varied and optimum solutions. Through a cyclical process of selection, reproduction, and variation, evolutionary algorithms simulate the dynamics of biological evolution to improve solutions within a computational framework. They operate by evolving a population of solutions through a 'natural selection' process, guided by an objective measure known as the 'fitness function,' which assesses each solution's suitability to the problem at hand. This fitness function is customised to the specifics of the problem being addressed.