ABSTRACT
Nature always provides some of the well-planned way to solve the real-life problems. Science is a conversation between the scientists/researchers and nature. The study of nature has progressed for thousands of years, advancing with innovative models, techniques, and tools and has established well-defined disciplines of scientific goals. Humankind has continuously attempted to understand nature by evolving innovative techniques and tools day by day. Genetic algorithms are regarded as the most popular technique in evolutionary algorithms. They mimic Charles Darwin’s principle of natural evolution. This chapter will focus on the growing area of genetic algorithms. The purpose is to present an in-depth analysis of genetic algorithms. Genetic algorithms are being utilized as adaptive algorithms for solving real-world problems and as a unique computational model of natural evolutionary systems. The chapter will give in-depth overview of genetic optimization, enabling researchers to derive simple genetic algorithms, and will also highlight the pros and cons of genetic algorithms.
