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Essentials of Metaheuristics (Second Edition) Paperback – December 20, 2012

4.4 4.4 out of 5 stars 24 ratings

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Interested in the Genetic Algorithm? Simulated Annealing? Ant Colony Optimization? Essentials of Metaheuristics covers these and other metaheuristics algorithms, and is intended for undergraduate students, programmers, and non-experts. The book covers a wide range of algorithms, representations, selection and modification operators, and related topics, and includes 71 figures and 135 algorithms great and small. Algorithms include: Gradient Ascent techniques, Hill-Climbing variants, Simulated Annealing, Tabu Search variants, Iterated Local Search, Evolution Strategies, the Genetic Algorithm, the Steady-State Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, Genetic Programming variants, One- and Two-Population Competitive Coevolution, N-Population Cooperative Coevolution, Implicit Fitness Sharing, Deterministic Crowding, NSGA-II, SPEA2, GRASP, Ant Colony Optimization variants, Guided Local Search, LEM, PBIL, UMDA, cGA, BOA, SAMUEL, ZCS, XCS, and XCSF.

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Product details

  • Publisher ‏ : ‎ Lulu.com; Second Edition (December 20, 2012)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 242 pages
  • ISBN-10 ‏ : ‎ 1300549629
  • ISBN-13 ‏ : ‎ 978-1300549628
  • Reading age ‏ : ‎ 1 year and up
  • Item Weight ‏ : ‎ 1.26 pounds
  • Dimensions ‏ : ‎ 8.5 x 0.55 x 10.98 inches
  • Customer Reviews:
    4.4 4.4 out of 5 stars 24 ratings

Customer reviews

4.4 out of 5 stars
24 global ratings

Top reviews from the United States

Reviewed in the United States on December 10, 2016
This is a very clever book, written in a very effective and informal style.

The author, Dr. Sean Luke, is a professor of computer science at George Mason University. The book is a compilation of notes, originating from teaching an undergraduate course on metaheuristics, nicely edited and presented. Dr. Luke uses a pseudo-code notation to support his description of each of about 150 algorithms covering a broad range of applications including searching, sorting, optimization, genetic algorithms, and combinatorics.

The code is language-independent and can easily be translated into the reader's language of choice. The descriptions are written in a very approachable and informal manner. I can easily imagine being a student in Dr. Luke's classes and enjoying every minute as he explains with knowledge and enthusiasm.
6 people found this helpful
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Reviewed in the United States on May 3, 2018
Very straightforward pseudo-code for a large number of useful algorithms. Reasonable advice on hyperparameterization and measuring the cost/benefits of different metaheuristic approaches.
Reviewed in the United States on June 8, 2015
Nice book, use it as introduction to Methaheuristics
One person found this helpful
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Reviewed in the United States on September 30, 2020
The only textbook I kept reading after the class ended. I took a class with Professor Sean Luke and this text is easy to reference and insightful to read.
2 people found this helpful
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Reviewed in the United States on January 5, 2022
Husband love it.
One person found this helpful
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Top reviews from other countries

Fant
5.0 out of 5 stars very great explainations of interesting ideas
Reviewed in Germany on April 30, 2016
i love this book, it explains complicated ideas in a very easy way.
great collection of approaches how one could find solutions in complex search-spaces.
Nathaniel Pryce
5.0 out of 5 stars The book has an excellent bibliography for further study
Reviewed in the United Kingdom on May 28, 2015
A very readable intro to the state of the art. Suitable for the professional programmer and academic alike. The book has an excellent bibliography for further study.