Part 1: The Basics of Genetic Algorithms
In this section, you will be introduced to the key concepts of genetic algorithms, beginning with the Darwinian evolution analogy, basic principles, and theoretical foundations. We will then dive deeper into the components and implementation details of these algorithms, exploring their flow and various methods of selection, crossover, and mutation. The section also focuses on real-coded genetic algorithms and advanced concepts such as elitism, niching, and sharing, all setting the stage for problem-solving in subsequent sections.
This part contains the following chapters:
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