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Essentials of Metaheuristics
About the Book
This 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.
What is a Metaheuristic?
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 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.
What is a Metaheuristic?
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.
237 pages, ebook
First published September 1, 2010
9 people are currently reading
80 people want to read
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Displaying 1 - 6 of 6 reviews
January 26, 2011
Nearly two months ago, someone recommended me this book on my blog, so I decided to read it. The level of details and the language the author uses to present all aspects of meta-heuristics as well as the number of real live examples makes this book a great position for everyone interested in meta-heuristics. Personally I'm working on a research project to understand behaviours of betting exchange markets and this book helped me to push my research in a good direction.
January 10, 2017
This is a great book on meta-heuristics. Very lucid! I specially like its treatment of co-evolutionary algorithms and tips on how to code an evolutionary computing system.
April 14, 2018
অনলাইন বই, হার্ডকপি পাওয়া যায়না!
বুয়েটে মাস্টার্সের জন্য পড়তে হচ্ছে। বইটা ভালো, অ্যালগরিদমের ছড়াছড়ি থাকলেও এর রিপ্রজেন্টেশন ভালো লাগছে!
বুয়েটে মাস্টার্সের জন্য পড়তে হচ্ছে। বইটা ভালো, অ্যালগরিদমের ছড়াছড়ি থাকলেও এর রিপ্রজেন্টেশন ভালো লাগছে!
March 17, 2025
Read it in full while working on EC projects. IT is a great summary and guide on the algorithms and ideas out there. Essential if one wants to implement some of them and wants a reference for such.
June 25, 2025
Great book on genetic algorithms and their relatives. Despite its brevity, it can at times feel like just a dry reference manual, especially the later chapters.
January 30, 2025
Forgot to record this set of lecture notes. Really enjoyed it and am making a repository of examples!
Displaying 1 - 6 of 6 reviews