woodys-uk
Price: £54.60
In stock
8 used & new from £29.95
See All Buying Options
Have one to sell? Sell yours here
 
 
How to Solve it: Modern Heuristics
 
 
Share your own customer images
Search inside another edition of this book

How to Solve it: Modern Heuristics (Hardcover)

by Z. Michalewicz (Author), David B. Fogel (Author) "This is not a book about algorithms ..." (more)
3.5 out of 5 stars  See all reviews (2 customer reviews)

Available from these sellers.


3 new from £54.59 5 used from £29.95
Other Editions: RRP: Our Price: Other Offers:
Hardcover (2nd ed. Revised and Extended) £39.99 £35.99 26 used & new from £27.00

Customers Viewing This Page May Be Interested in These Sponsored Links

  (What is this?)
   How to Solve It opens new browser window
www.artofproblemsolving.com  -  Unique Math Books and Forums Thousands of Users Worldwide 
   Solve opens new browser window
Ask.com  -  Find the Best Results for Solve! 
  
 

Customers Who Bought This Item Also Bought

How to Solve it: A New Aspect of Mathematical Method (Penguin Science)

How to Solve it: A New Aspect of Mathematical Method (Penguin Science)

by George Polya
5.0 out of 5 stars (2)  £7.18
Combinatorial Optimization: Algorithms and Complexity

Combinatorial Optimization: Algorithms and Complexity

by Christos H. Papadimitriou
5.0 out of 5 stars (2)  £10.74
Thinking Mathematically

Thinking Mathematically

by John Mason
4.8 out of 5 stars (6)  £30.89
Ant Colony Optimization

Ant Colony Optimization

by M Dorigo
£30.35
Pandora's Box: Social and Professional Issues of the Information Age

Pandora's Box: Social and Professional Issues of the Information Age

by Andrew A. Adams
5.0 out of 5 stars (1)  £29.39
› Explore similar items

Product details

  • Hardcover: 467 pages
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. K; illustrated edition edition (Nov 1999)
  • Language English
  • ISBN-10: 3540660615
  • ISBN-13: 978-3540660613
  • Product Dimensions: 24.1 x 16.5 x 3 cm
  • Average Customer Review: 3.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon.co.uk Sales Rank: 835,142 in Books (See Bestsellers in Books)

    •  Would you like to update product info or give feedback on images?

  • See Complete Table of Contents

Product Description

Product Description

This book is the only source that provides comprehensive, current, and correct information on problem solving using modern heuristics. It covers classic methods of optimization, including dynamic programming, the simplex method, and gradient techniques, as well as recent innovations such as simulated annealing, tabu search, and evolutionary computation. Integrated into the discourse is a series of problems and puzzles to challenge the reader. The book is written in a lively, engaging style and is intended for students and practitioners alike. Anyone who reads and understands the material in the book will be armed with the most powerful problem solving tools currently known.
Inside This Book (Learn More)
Browse and search another edition of this book.
First Sentence
This is not a book about algorithms. Read the first page
Explore More
Concordance
Browse Sample Pages
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
Search inside this book:

Suggested Tags from Similar Products

 (What's this?)
Be the first one to add a relevant tag (keyword that's strongly related to this product)
 
mathematical methods
cognitive science

Your tags: Add your first tag
 
See most popular tags

What Do Customers Ultimately Buy After Viewing This Item?

How to Solve it: Modern Heuristics
67% buy the item featured on this page:
How to Solve it: Modern Heuristics 3.5 out of 5 stars (2)
How to Solve it: A New Aspect of Mathematical Method (Penguin Science)
16% buy
How to Solve it: A New Aspect of Mathematical Method (Penguin Science) 5.0 out of 5 stars (2)
£7.18
Combinatorial Optimization: Algorithms and Complexity
11% buy
Combinatorial Optimization: Algorithms and Complexity 5.0 out of 5 stars (2)
£10.74
The Algorithm Design Manual
4% buy
The Algorithm Design Manual 4.5 out of 5 stars (6)
£27.48
Explore similar items
 

Customer Reviews

2 Reviews
5 star:    (0)
4 star:
 (1)
3 star:
 (1)
2 star:    (0)
1 star:    (0)
 
 
 
 
 
Average Customer Review
3.5 out of 5 stars (2 customer reviews)
 
 
 
 
Share your thoughts with other customers:
Most Helpful Customer Reviews

 
13 of 14 people found the following review helpful:
4.0 out of 5 stars Wide, deep and good fun. Well worth reading., 19 Mar 2001
By A Customer
Although a text book, this book is fun. It is both a good review of evolutionary algorithms and an excellent introduction to problem solving.

Algorithms are not in general given in full and there is no source code, so you will still have to put some effort in if you have a real problem to solve. However this is one of the points of the book: real problems are complex, you can't just use a recipe.

Coverage of other search methods such as neural nets is not so extensive, but there is reasonable coverage of more traditional methods.

On top of all this, there are numerous problem solving problems. These are all good fun and need nothing more than paper and pen.

A good book for the train and for the library. And there arn't many of those.

Comment Comment | Permalink | Was this review helpful to you? Yes No (Report this)



 
3.0 out of 5 stars Underwhelming, 24 Sep 2009
This review is from: How to Solve It: Modern Heuristics (Hardcover)
Having read a couple of very positive reviews, I was looking forward to this, but now that it is here, and I've had a chance to read it, I'm very disappointed. It strikes me as pretty shallow, and it definitely takes the name of Georg Polya in vain. (Michaelewicz also writes 'business-oriented' books on decision support - you can tell). It certainly has little, conceptually, to do with Polya's 'How to solve it' (in fact, given the complete lack of any formal theoretical development, the authors are lucky that the man is safely dead). A more accurate title would be 'a bunch of stuff on optimisation, mostly about genetic algorithms and traveling salesman problems, but with a bit on neural nets and fuzzy logic thrown in'. These three technologies used to get sexy articles in the popular computer press about 10 to 20 years ago. It is interesting why the three always seem to crop up together, but they do - or at least they did.

Anyway, the core agenda, which is not heuristics, does poke out at various points. On page 190 there is a revealing passage bout the elusive 'Holy Grail' of 'a perfect evolutionary algorithm for the TSP [Travelling Salesman Problem]'. Now, the world in general would be fascinated by a polynomial solution to the TSP, but the world in general - sorry to say - doesn't actually give a toss if that solution is evolutionary.*

As I said, I was unhappy about the complete lack of real theoretical background which would put any of the discussed methods in perspective/context. The discussion of simulated annealing, for instance, is absent any of the underlying (and powerful) intuitions from statistical physics which, if nothing else, makes the technique much richer, and not conceptually comparable to, tabu search, with which it is discussed in parallel. As far as I can see, the latter is an isolated hack - empirically it may be effective in some applications, but it is not part of a larger conceptual framework. At least if it is not an isolated hack, then the authors provide no evidence - I note that it gets all of three lines in Russell and Norvig.

More seriously, there isn't even any well-founded discussion of mathematical models of evolution. All that I could find was essentially a citation - not even a discussion - of the 'no free lunch' theorems. No Maynard-Smith, no Kondrashov, not even Hopfield's '78 paper - though other later stuff by Hopfield is cited. And without this - and without a lot of other formal theory stuff as well, if I were being honest - there is no hope of a methodological framework. After all, computers are, unavoidably, formal machines. In the end, the evolutionary models that are discussed are not a lot more than a bunch of gadgets, and the authors are reduced to saying that for your own problems, you are going to have to think up your own gadgets. This, to be blunt, is why evolutionary computing remains a niche research area.

A separate problem is the lack of any perspective w.r.t. other, today more commonly used, technologies that address similar problems. The discussion of neural networks and pattern classification does not mention, e.g., that the benchmark classifier technology today is vector support machines, which substantially outperform neural networks. Or that the standard technology for exploring complex function spaces is Monte-Carlo analysis (strictly, a lot of the techniques that are discussed in the book _are_ actually Monte-carlo methods of one sort or another). This does not mean that the methods discussed are _not_ interesting, just that without a perspective, it is difficult to say whether they are appropriate tools for a job.

In the end it was not clear to me who this book is really aimed at. It is certainly not aimed at me. Senior undergraduates in something like operations research might be a target, but I personally would not use it for a CS or applied math class. And I cannot, honestly, forsee it being a lot of use to me outside the classroom.

*Which anyway, a priori, seems unlikely, since idealised recombinatory evolutionary strategies show rapid information gain (N^1/2) in the size of the genome in suboptimal situations, but near the optimum, parthenogenesis with mutation is a better strategy.
Comment Comment | Permalink | Was this review helpful to you? Yes No (Report this)


Share your thoughts with other customers: Create your own review
 
 
 
Only search this product's reviews


Customer Discussions

This product's forum
Discussion Replies Latest Post
No discussions yet

Ask questions, Share opinions, Gain insight
Start a new discussion
Topic:
First post:
Prompts for sign-in
 


Active discussions in related forums
   
Related forums

Listmania!

Create a Listmania! list

Look for similar items by category

Look for similar items by subject























i.e., each product must be in subject 1 AND subject 2 AND ...

Feedback

Ad

Your Recent History

 (What's this?)

After viewing product detail pages or search results, look here to find an easy way to navigate back to pages you are interested in.