- Genetic Algorithms Tutorial
- Genetic Algorithms – Home
- Genetic Algorithms – Introduction
- Genetic Algorithms – Fundamentals
- Genotype Representation
- Genetic Algorithms – Population
- Genetic Algorithms – Fitness Function
- Genetic Algorithms – Parent Selection
- Genetic Algorithms – Crossover
- Genetic Algorithms – Mutation
- Survivor Selection
- Termination Condition
- Models Of Lifetime Adaptation
- Effective Implementation
- Advanced Topics
- Application Areas
- Further Readings
- Genetic Algorithms Resources
- Genetic Algorithms - Quick Guide
- Genetic Algorithms - Resources
- Genetic Algorithms - Discussion
- Selected Reading
- UPSC IAS Exams Notes
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Genetic Algorithms Tutorial
This tutorial covers the topic of Genetic Algorithms. From this tutorial, you will be able to understand the basic concepts and terminology involved in Genetic Algorithms. We will also discuss the various crossover and mutation operators, survivor selection, and other components as well.
Also, there will be other advanced topics that deal with topics like Schema Theorem, GAs in Machine Learning, etc. which are also covered in this tutorial.
After going through this tutorial, the reader is expected to gain sufficient knowledge to come up with his/her own genetic algorithms for a given problem.
This tutorial is prepared for the students and researchers at the undergraduate/graduate level who wish to get “good solutions” for optimization problems “fast enough” which cannot be solved using the traditional algorithmic approaches.
Genetic Algorithms is an advanced topic. Even though the content has been prepared keeping in mind the requirements of a beginner, the reader should be familiar with the fundamentals of Programming and Basic Algorithms before starting with this tutorial.