Home » Others » Essentials of Metaheuristics

Essentials of Metaheuristics

Essentials of Metaheuristics

Metaheuristics is a common but unfortunate name for any stochastic optimization algorithm intended to be the last resort before giving up and using random or brute-force search. Such algorithms are used for problems where you don't know how to find a good solution, but if shown a candidate solution, you can give it a grade. The algorithmic family includes genetic algorithms, hill-climbing, simulated annealing, ant colony optimization, particle swarm optimization, and so on.

This book is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts. It was developed as a series of lecture notes for an undergraduate course I taught at GMU. The chapters are designed to be printable separately if necessary. As it's lecture notes, the topics are short and light on examples and theory. It's best when complementing other texts. With time, I might remedy this.

Pages : 242 pages
File type : pdf
Downloads: 1
Submitted On: 2020-08-29
License: CC BY-ND 3.0 US
Author(s): Sean Luke

Take advantage of this course called Essentials of Metaheuristics to improve your Others skills and better understand Metaheuristics.

This course is adapted to your level as well as all Metaheuristics pdf courses to better enrich your knowledge.

All you need to do is download the training document, open it and start learning Metaheuristics for free.

This tutorial has been prepared for the beginners to help them understand basic Metaheuristics Others. After completing this tutorial you will find yourself at a moderate level of expertise in Metaheuristics from where you can take yourself to next levels.

This tutorial is designed for Metaheuristics students who are completely unaware of Metaheuristics concepts but they have basic understanding on Others training.

Download

Tutorials in the same categorie :