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Rating: 
Summary: Well-balanced and enjoyable
Review: This was both a good introduction to genetic algorithms in general and to their adaptation to grouping problems in particular. More than that the style is concise, engaging and consistently interesting. The explanations are practical and intuitively appealing. I found myself jumping around in the book somewhat (I would recommend reading chapter 14 before chapter 1), but everything was explained somewhere. At the end, I felt I had a good basis not just from which to implement a grouping GA, but to consider many other variations or developments from the classic model. The key strength of this book for me was its practical, common-sense approach that stresses understanding the problem and if it works use it, if not adapt it so it does. Rather the spirit of GAs themselves.
Rating:
Summary: Well-balanced and enjoyable
Review: This was both a good introduction to genetic algorithms in general and to their adaptation to grouping problems in particular. More than that the style is concise, engaging and consistently interesting. The explanations are practical and intuitively appealing. I found myself jumping around in the book somewhat (I would recommend reading chapter 14 before chapter 1), but everything was explained somewhere. At the end, I felt I had a good basis not just from which to implement a grouping GA, but to consider many other variations or developments from the classic model. The key strength of this book for me was its practical, common-sense approach that stresses understanding the problem and if it works use it, if not adapt it so it does. Rather the spirit of GAs themselves.
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