Search Methodologies is a tutorial survey of the methodologies that are at the confluence of several fields: Computer Science, Mathematics and Operations Research. It is a carefully structured and integrated treatment of the major technologies in optimization and search methodology. The book is made up of 19 chapters. The chapter authors are drawn from across Computer Science and Operations Research and include some of the world's leading authorities in their field.The result is a major state-of-the-art tutorial text of the main optimization and search methodologies available to researchers, students and practitioners across discipline domains in applied science. It can be used as a textbook or a reference book to learn and apply these methodologies to a wide range of today's problems. It has been written by some of the world's most well known authors in the field.
Author(s): Edmund K. Burke, Graham Kendall
Publisher: Springer
Year: 2005
Language: English
Pages: 617
front-matter......Page 1
01Introduction......Page 10
02Classical Techniques......Page 24
03Integer Programming......Page 74
04Genetic Algorithms......Page 101
05Genetic Programming......Page 130
06Tabu Search......Page 168
07Simulated Annealing......Page 190
08Variable Neighborhood Search......Page 214
09Constraint Programming......Page 242
10Multi-Objective Optimization......Page 276
11Complexity Theory and the No Free Lunch Theorem......Page 320
12Machine Learning......Page 343
13Artificial Immune Systems......Page 376
14Swarm Intelligence......Page 401
15Fuzzy Reasoning......Page 436
16Rough Set Based Decision Support......Page 474
17Hyper-Heuristics......Page 527
18Approximation Algorithms......Page 555
19Fitness Landscapes......Page 584
back-matter......Page 608
