Most evolutionary computation or math books deal with the techniques of solving problems. This book teachs you how to think of a solution for the problem you face, and not what problems are appropriate for the technique in hand.

The logic is that when you do a craft work, you do pick the appropriate tool from your tools box, but you don't grasp a tool and then find a job to go with it, which is the case when you can only handle this tool.

The authors have updated their successful first edition, though the latter, printed in 99, was scarcely obsolete. A heuristic can be basically a rule of thumb, dressed up in fancier language. What the authors intend is for you to develop an intuition about when to use modern algorithms. Where is almost every case, these are actually implemented on a computer; a reflection of the cheap availability of computing power to most readers.

The book is a good complement to various standard algorithm texts, like those by Sedgewick, Aho and Knuth. You can consider this book as standing a level above those. [Though Knuth's books also do an excellent job of suggesting when to use or modify algorithms. ]

The level of discussion here is not of a strict, heavy mathematical approach. It can be read as informal guidelines, that discuss the gist of such ideas as simulated annealing and evolutionary methods. There is a wide range of example problems, to motivate you in understanding what might be used to solve them.

i have not finished reading this book, but it's 'worth it' if only for the first two chapters! :) anyone interested in dynamical systems (control aspects), general problem solving, AI, and human thinking should read and understand this book! :) work the problems! :) think! enjoy! :)

This is simply the best book on computer problem solving that I've seen. I have both editions. The second is expanded from the first with new material on things like multicriteria decision making. The book's engaging tone is matched by a detailed understanding of all the different approaches to problem solving that are offered. The text emphasizes evolutionary computing but offers complete treatments of other optimization methods, although there are only single chapters on neural nets or fuzzy logic. Most importantly, it does so in a way that no other book I've seen does -- it makes it fun and it makes you think! I saw that another reviewer said the book got great classroom reviews. I don't doubt it. I wish there was a book like this when I was in college.