Genetic Algorithm and Application

Abstract

In the realms of science and engineering, genetic algorithms have established themselves as versatile algorithms, capable of tackling a diverse range of practical problems and serving as computational models that mirror the intricate mechanisms of natural evolutionary systems. They are considered as a search-based technique based on the principles of Genetics and Natural Selection used in computing to find an exact or approximate solution for optimization and search problems. Genetic algorithms are also termed as heuristic search algorithms that belong to the larger part of evolutionary algorithms. They are inspired by evolutionary biology such as selection, cross over, and inheritance mutation. These algorithms provide a technique for the program to automatically improve the class of their parameters and generate high-quality solutions for optimization problems and search problems . This paper is an introduction of the Genetic algorithm approach and briefly describes some of the most interesting research or applications which are used in real-world projects that enable readers to implement and experiment with Genetic Algorithm on their own.