How to Solve it: Modern Heuristics

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. This second edition contains two new chapters, one on coevolutionary systems and one on multicriterial decision-making. Also some new puzzles are added and various subchapters are revised.

 Preface.- Introduction.- 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 is Taller? 15. Multicriteria Decision-Making. XVI. Do You Like Simple Solutions? 16. Hybrid Systems.- 17. Summary.- Appendices.- References.- Index.