Drawing its inspiration from Charles Darwin's theory of natural evolution, one of the most fascinating techniques for problem-solving is the algorithm family suitably named evolutionary computation. Within this family, the most prominent and widely used branch is known as genetic algorithms. This chapter is the beginning of your journey to mastering this extremely powerful, yet extremely simple, technique.
In this chapter, we will introduce genetic algorithms and their analogy to Darwinian evolution, and dive into their basic principles of operation as well as their underlying theory. We will then go over the differences between genetic algorithms and traditional ones and cover the advantages and limitations of genetic algorithms and their uses. We will conclude by reviewing the cases where the use of a genetic algorithm may prove beneficial.
In this introductory chapter, we will cover the following topics:
- What are genetic algorithms?
- The theory behind genetic algorithms
- Differences between genetic algorithms and traditional algorithms
- Advantages and limitations of genetic algorithms
- When to use genetic algorithms
