School of Information Technology and Engineering, School of Computer Sciences and Engineering, VIT University, Vellore
Online published on 21 March, 2018.
Code optimization has always been a critical area for both programmers and researchers alike. Minimizing the code execution time and code size have the highest priority in code optimizations. Genetic Algorithm is a kind of technique that is employed in order to solve optimization problems. The main idea behind the genetic algorithm is exactly like the law of the jungle “Survival of the Fittest”; It is evolutionary; We keep on working towards getting better and improved solutions till we get an optimal/best solution. The main tasks or operations performed by the genetic algorithm are selection and crossover along with mutation which we will discuss in length. Genetic algorithm mainly uses the following operations which are Encoding, Selection, Crossover, and mutation. Genetic Algorithms are used in a wide array of fields and have lots of applications.
