Search Methodologies: introductory Tutorials in Optimization and Decision Support Techniques

Foreword; Fred Glover

Preface

Chapter 1: Introduction; Edmund Burke and Graham Kendall

Chapter 2: Classical Techniques; Kathryn Dowsland

Chapter 3: Integer Programming; Bob Bosch and Michael Trick

Chapter 4: Genetic Algorithms; Kumara Sastry, David Goldberg, and Graham Kendall

Chapter 5: Genetic Programming; John Koza and Riccardo Poli

Chapter 6: Tabu Search; Michael Gendreau and Jean-Yves Potvin

Chapter 7: Simulated Annealing; Emile Aarts, Jan Korst and Wil Michiels

Chapter 8: Variable Neighborhood Search; Pierre Hansen and Nenad Mladenovic

Chapter 9: Constraint Programming; Eugene Freuder and Mark Wallace

Chapter 10: Multi-Objective Optimization; Kalyanmoy Deb

Chapter 11: Complexity Theory and The No Free Lunch Theorem; Darrell Whitley and Jean Paul Watson

Chapter 12:Machine Learning; Xin Yao and Yong Liu

Chapter 13: Artificial Immune Systems; Uwe Aickelin and Dipankar Dasgupta

Chapter 14: Swarm Intelligence; Daniel Merkle and Martin Middendorf

Chapter 15: Fuzzy Reasoning; Costas Pappis and Constantinos Siettos

Chapter 16: Rough Set Based Decision Support; Roman Slowinski, Salvatore Greco and Benedetto Matarazzo

Chapter 17: Hyper-heuristics; Peter Ross

Chapter 18:Approximation Algorithms; Carla Gomes and Ryan Williams

Chapter 19: Fitness Landscapes; Colin Reeves