Genetic Algorithm

Objective: A population of input parameters is generated randomly. These parameters are asessed and the most fit ones are chosen for further computation by applying these to a fitness function. The ones that are more fit have higher probability of being picked. These picked ones then undergo crossover in order to obtain new ones.…