Search Methodologies

Edited by Edmund K. Burke and Graham Kendall

in Springer Books from Springer

Date: 2005
ISBN: 978-0-387-28356-2
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Chapters in this book:

Ch Chapter 1 Introduction

Edmund K. Burke and Graham Kendall

Ch Chapter 10 Multi-Objective Optimization

Kalyanmoy Deb

Ch Chapter 11 Complexity Theory and the No Free Lunch Theorem

Darrell Whitley and Jean Paul Watson

Ch Chapter 12 Machine Learning

Xin Yao and Yong Liu

Ch Chapter 13 Artificial Immune Systems

Uwe Aickelin and Dipankar Dasgupta

Ch Chapter 14 Swarm Intelligence

Daniel Merkle and Martin Middendorf

Ch Chapter 15 Fuzzy Reasoning

Costas P. Pappis and Constantinos I. Siettos

Ch Chapter 16 Rough Set Based Decision Support

Roman Slowinski, Salvatore Greco and Benedetto Matarazzo

Ch Chapter 17 Hyper-Heuristics

Peter Ross

Ch Chapter 18 Approximation Algorithms

Carla P. Gomes and Ryan Williams

Ch Chapter 19 Fitness Landscapes

Colin R. Reeves

Ch Chapter 2 Classical Techniques

Kathryn A. Dowsland

Ch Chapter 3 Integer Programming

Robert Bosch and Michael Trick

Ch Chapter 4 Genetic Algorithms

Kumara Sastry, David Goldberg and Graham Kendall

Ch Chapter 5 Genetic Programming

John R. Koza and Riccardo Poli

Ch Chapter 6 Tabu Search

Michel Gendreau and Jean-Yves Potvin

Ch Chapter 7 Simulated Annealing

Emile Aarts, Jan Korst and Wil Michiels

Ch Chapter 8 Variable Neighborhood Search

Pierre Hansen and Nenad Mladenović

Ch Chapter 9 Constraint Programming

Eugene C. Freuder and Mark Wallace

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DOI: 10.1007/0-387-28356-0

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