Book Image

C# Data Structures and Algorithms - Second Edition

By : Marcin Jamro
Book Image

C# Data Structures and Algorithms - Second Edition

By: Marcin Jamro

Overview of this book

Building your own applications is exciting but challenging, especially when tackling complex problems tied to advanced data structures and algorithms. This endeavor demands profound knowledge of the programming language as well as data structures and algorithms – precisely what this book offers to C# developers. Starting with an introduction to algorithms, this book gradually immerses you in the world of arrays, lists, stacks, queues, dictionaries, and sets. Real-world examples, enriched with code snippets and illustrations, provide a practical understanding of these concepts. You’ll also learn how to sort arrays using various algorithms, setting a solid foundation for your programming expertise. As you progress through the book, you’ll venture into more complex data structures – trees and graphs – and discover algorithms for tasks such as determining the shortest path in a graph before advancing to see various algorithms in action, such as solving Sudoku. By the end of the book, you’ll have learned how to use the C# language to build algorithmic components that are not only easy to understand and debug but also seamlessly applicable in various applications, spanning web and mobile platforms.
Table of Contents (13 chapters)

Title guess

It is high time to change a type of applied algorithm to a heuristic one, which has many applications and also subtypes. Here, we focus only on genetic algorithms, which are adaptive heuristic search algorithms. They are related to the Darwinian theory of evolution and natural selection. According to it, individuals in a population compete, and the population evolves to create next generations that are better suited to survive. The genetic algorithms operate on strings that evolve to receive possibly the highest value of fitness, complying with the rule of survival and passing on the genes of the fittest parents, also based on a randomized data exchange. The algorithm ends its operation when a suitable value of fitness is reached or when the maximum number of generations is reached.

Where can you find more information?

You can find a lot of content about genetic algorithms in the internet, such as in the article published at https://link.springer.com/article/10.1007...