Genetic Programming and Evolvable Machines

, Volume 12, Issue 3, pp 333–334 | Cite as

Sean Luke: essentials of metaheuristics

  • Michael LonesEmail author
Book Review

Many of us cut our evolutionary teeth on such classics as David Goldberg’s Genetic Algorithms in Search, Optimisation and Machine Learning, Melanie Mitchell’s An Introduction to Genetic Algorithms, and Zbigniew Michalewicz’s Genetic Algorithms + Data Structures = Evolution Programs. At the time, these were excellent books. However, a lot has happened in the field over the last couple of decades, and the time is ripe for new textbooks introducing the state of the art in evolutionary algorithms.

It is too early to say whether Sean Luke’s Essentials of Metaheuristics will become another classic, but it certainly shows a lot of promise. The author describes it as a ‘set of undergraduate lecture notes’. This may be what Sean Luke uses it for (and he provides syllabi suggestions for those who wish to follow in his footsteps), but I would recommend it to anyone working in the field, especially those who are involved with the nitty–gritty of implementing evolutionary algorithms.

The scope of...

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.University of YorkYorkUK

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