Chapter 5 Selecting the Best

Genetic Algorithms in Elixir — by Sean Moriarity (43 / 101)

👈 What You Learned | TOC | Exploring Selection 👉

In the last chapter, you learned how to evaluate solutions using fitness functions. Remember, fitness functions measure the viability of a solution. Fitness functions are an important aspect of your genetic algorithm, but they mean nothing if you don’t do anything with them. With your population evaluated, and each chromosome assigned a fitness, it’s time to perform selection.

If you’ve ever been on a team, you understand the importance of having the right people. Whether it be in sports, music, work, or any collaboration, choosing the right people to fill positions and complement other members is vital to the success of the organization. This idea of selecting the right people to fill the right roles directly correlates to selection in genetic algorithms.

Selection is the first genetic operator in an evolution. On the surface, selection is responsible for choosing chromosomes that will reproduce in the next step. At its core, selection is responsible for ensuring the next generation of chromosomes is even stronger than the last.

Charles Darwin’s theory of evolution suggests that strong traits that are key to survival become more common in successive generations. Whether you believe in evolution or not, the idea of natural selection is a key aspect of genetic algorithms.

In the context of genetic algorithms, the process of selection is better described as artificial selection. It’s important to note the distinction between natural and artificial selection. In the case of genetic algorithms, you have the ability to define your selection and fitness criteria whereas in nature, selection is nondeterministic, and fitness is an emergent property of selection. That is to say the process of selection comes before the determination of fitness. In a genetic algorithm, you have the power to select which traits of a solution correlate to it’s fitness and the power to select based on this fitness criteria, thus you have the power to determine which traits persist between generations. Note the process differs between natural selection because, in nature, fitness cannot be determined until after selection takes place.

Artificial selection gives you the power to choose which traits are important to your problem. To think about this more concretely, imagine…

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