Understanding Mutation
Learn how mutation works and look at some properties of mutation.
We'll cover the following...
Mutation in genetic algorithms
As with most of the other aspects of a genetic algorithm, mutation has a loose analogy to a real biological process. In biology, mutation is a random change in an individual’s DNA sequence that often manifests itself in physical traits. For example, blue eyes are a genetic mutation.
Mutation in genetic algorithms works in much the same way. It’s a random change to some or all of the genes in a chromosome. The purpose of mutation is to introduce genetic diversity into the population.
Recall that the algorithm we wrote to solve the One-Max problem in the lesson The Evaluation, Selection and Crossover Steps, struggled to find the best solution until we added mutation. When dealing with binary genotypes, premature convergence is more common because genes can only take on one of ...