Most Helpful Customer Reviews
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6 of 6 people found the following review helpful:
5.0 out of 5 stars
Excellent Text book, 3 April 2000
By A Customer
I have chosen this book as the main textbook for my masters course "Modern Heuristic Techniques", Computer Science, Australian Defence Force Academy, UC, University of New South Wales. The book puts together, in an excellent way, recent advances in the theory of heuristic search. Although the title emphasises optimisation, the prospective reader should be aware of the fact that problems in many domains (such as machine learning, conventional operational research, speech recognition, ... Etc.) are optimisation problems in the first place. While I was struggling to collect easy-to-understand papers for my students, this book came to save my time, my efforts, as well as my students. It was important for me to find a textbook, which covers non-conventional topics such as GA, EA, SA, ... Etc. Being written by the people who invented the novel techniques, this book matched all my expectations. Apart from minor personal comments on the presentation of some algorithms, the book is very well presented. I do encourage people teaching for post-graduates in the fields of operational research, machine learning, search, ... Etc, to use this book for their course. Finally, I would like to thank Mc-Graw Hill for their prompt delivery of the book and David Corne for his help.
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5 of 5 people found the following review helpful:
5.0 out of 5 stars
Synopsis as given by McGraw-Hill, 13 Jan 2000
As I am one of the contributors of this book I should not be the one who provides a rating because I am biased. I feel, though that the information provided about the book is insufficient and therefore I would like to provide the information as given by the publisher McGraw-Hill (if this is permitted).Synopsis: Optimisation is a pivotal aspect of software design. The techniques treated in this book represent the leading edge of research as elucidated by the leading researchers, many of whom are the originators of the methods. The volume editors are experienced and respected researchers and the subject is one of growing interest in advanced undergraduate and postgraduate programmes.There are a collection of well-known modern optimisation methods being researched and applied to real problems worldwide. These include a variety of local search methods (hillclimbing, simulated annealing, tabu search, ...) and so-called evolutionary computation methods (genetic algorithms, genetic programming, evolutionary programming...). In recent years, a range of novel ideas have emerged in this research community, proposing new algorithms which are interestingly different from the current well-studied crop. In particular, these new ideas include: Ant Colony based optimisation, Scatter Search, Differential Evolution, Immune System Methods, Optima Linking, and Parallel Distributed Genetic Programming. Key Features: Tutorial approach with examples and problems| Detailed algorithms in pseudocode Contents: Section 1: Ant Colony Optimisation; Section 2: Differential Evolution; Section 3: Scatter Search and Path Relinking; Section 4: Immune System Methods; Section 5: Memetic Algorithms; Section 6: Emerging Techniques and Extensions: Parallel Distributed Genetic Programming; Co-evolutionary methods; Guided Local Search; Stepwise Adaptive Weight Algorithms; Particle Swarm Methods
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5.0 out of 5 stars
New Ideas in Optimisation, 31 Oct 2002
The book presents in an elegant stile wide range of optimisation techniques. Suitable for studding and practising of advanced heuristic algorithms for optimisation as Ant Colony Optimisation, Differential Evolution, Immune System Methods, Mimetic Algorithms and Particle Swarm Optimisation. Even issued 1999 the book provides a sufficient basis of knowledge in that matter.
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