What You Learned

Genetic Algorithms in Elixir — by Sean Moriarity (69 / 101)

👈 Local Versus Global Reinsertion | TOC | Chapter 9 Tracking Genetic Algorithms 👉

In this chapter, you learned about reinsertion and different types of reinsertion strategies. You learned how to implement different reinsertion strategies, and you analyzed the impacts of different reinsertion strategies on a scheduling problem.

You also learned how you can grow and shrink your population — and do so without falling into the traps of exponential decay and growth.

Finally, you learned about local reinsertion and local populations and how they differ from global reinsertion strategies and global genetic algorithms.

In the next chapter, you’ll step away from the internals of a genetic algorithm and instead focus on how you can track how fitness, age, and other metrics change during evolutions. Rather than focus on improving your algorithms and learning new techniques, you’ll learn how to compare performance between algorithms and better track the progress of an algorithm.

Copyright © 2021, The Pragmatic Bookshelf.

👈 Local Versus Global Reinsertion | TOC | Chapter 9 Tracking Genetic Algorithms 👉

Genetic Algorithms in Elixir by Sean Moriarity can be purchased in other book formats directly from the Pragmatic Programmers. If you notice a code error or formatting mistake, please let us know here so that we can fix it.