E-Book, Englisch, 467 Seiten, eBook
Michalewicz / Fogel How to Solve It: Modern Heuristics
2000
ISBN: 978-3-662-04131-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 467 Seiten, eBook
ISBN: 978-3-662-04131-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book is the only source that provides a systematic, integrated introduction to problem solving using modern heuristics, presenting the state-of-the-art in both numerical and analytic methods. 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. Written in a lively, engaging style, readers will learn how to use some of the most powerful problem solving tools currently available.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
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 Do You Like Simple Solutions?.- 14 Hybrid Systems.- 15 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.
