The Genetic Algorithm (GA) in Relation to Natural Evolution
Pawan Shivan Othman, Rasheed Reber Ihsan, Reving Masoud Abdulhakeem
Abstract
For optimizing search global solution for complicated issues the Genetic Algorithm (GA) is a famous evolutionary computation technique that plays an important role in finding meaningful solutions to hard problems with a huge search space could be a process based on genetic selection ideas. In addition, it supports machine learning causes, as well as study and evolution. However, developing genetic processes that were formerly significant to a random population, which might be started by biology for chromosomal production with factors like selection, crossover, and mutation. The aim of going through this GA process is to find a solution for consecutive generations. In individual production there has been an extent success instantly in ratio to fitness which is suited for it, as a result successive generation will be better in one condition, which is ensuring the quality. Furthermore, John Holland is considered as being the funding father of the initial genetic algorithm, with a funding date in the 1970s. in this paper we have explained what a genetic algorithm is, its key operations, and how it works as well as its features and applications.