How to Solve It: Modern Heuristics
2nd Edition
Published on 21. September 2004
Book
Hardback
XVI, 554 pages
978-3-540-22494-5 (ISBN)
Description
No pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.
More details
Edition
Second Edition 2004
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Professional/practitioner
Edition type
Revised edition
Illustrations
XVI, 554 p.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 37 mm
Weight
1021 gr
ISBN-13
978-3-540-22494-5 (9783540224945)
DOI
10.1007/978-3-662-07807-5
Schweitzer Classification
Other editions
Additional editions
Zbigniew Michalewicz | David B. Fogel
How to Solve It: Modern Heuristics
E-Book
03/2013
2nd Edition
Springer
€69.54
Available for download
Zbigniew Michalewicz | David B. Fogel
How to Solve It: Modern Heuristics
Book
12/2010
2nd Edition
Springer
€69.54
Shipment within 7-9 days
Previous edition
Book
01/2002
Springer
€85.59
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Persons
Dr. Edwin F. Meyer is an Associate Professor and Chair of the Department of Physics and Astronomy at Baldwin Wallace University, Berea, OH, USA.
Dr. Nickolas Falkner is a Senior Lecturer and Associate Dean of Information Technology in the School of Computer Science at the University of Adelaide, Australia.
Dr. Raja Sooriamurthi is an Associate Teaching Professor in the Information Systems Program at Carnegie Mellon University, Pittsburgh, PA, USA.
Dr. Zbigniew Michalewicz is an Emeritus Professor of the School of Computer Science at the University of Adelaide, Australia. He also holds Professor positions at the Institute of Computer Science, Polish Academy of Sciences and at the Polish-Japanese Institute of Information Technology.
Content
I What Are the Ages of My Three Sons?.- 1 Why Are Some Problems Difficult to Solve?.- II How Important Is a Model?.- 2 Basic Concepts.- III What Are the Prices in 7-11?.- 3 Traditional Methods - Part 1.- IV What Are the Numbers?.- 4 Traditional Methods - Part 2.- V What's the Color of the Bear?.- 5 Escaping Local Optima.- VI How Good Is Your Intuition?.- 6 An Evolutionary Approach.- VII One of These Things Is Not Like the Others.- 7 Designing Evolutionary Algorithms.- VIII What Is the Shortest Way?.- 8 The Traveling Salesman Problem.- IX Who Owns the Zebra?.- 9 Constraint-Handling Techniques.- X Can You Tune to the Problem?.- 10 Tuning the Algorithm to the Problem.- XI Can You Mate in Two Moves?.- 11 Time-Varying Environments and Noise.- XII Day of the Week of January 1st.- 12 Neural Networks.- XIII What Was the Length of the Rope?.- 13 Fuzzy Systems.- XIV Everything Depends on Something Else.- 14 Coevolutionary Systems.- XV Who's Taller?.- 15 Multicriteria Decision-Making.- XVI Do You Like Simple Solutions?.- 16 Hybrid Systems.- 17 Summary.- Appendix A: Probability and Statistics.- A.1 Basic concepts of probability.- A.2 Random variables.- A.2.1 Discrete random variables.- A.2.2 Continuous random variables.- A.3 Descriptive statistics of random variables.- A.4 Limit theorems and inequalities.- A.5 Adding random variables.- A.6 Generating random numbers on a computer.- A.7 Estimation.- A.8 Statistical hypothesis testing.- A.9 Linear regression.- A.10 Summary.- Appendix B: Problems and Projects.- B.1 Trying some practical problems.- B.2 Reporting computational experiments with heuristic methods.- References.