Search Methodologies

Edited by Edmund K. Burke () and Graham Kendall ()

in Springer Books from Springer

Date: 2014
Edition: 2nd ed. 2014
ISBN: 978-1-4614-6940-7
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Chapters in this book:

Ch Chapter 1 Introduction

Edmund K. Burke and Graham Kendall

Ch Chapter 10 Simulated Annealing

Emile Aarts, Jan Korst and Wil Michiels

Ch Chapter 11 GRASP: Greedy Randomized Adaptive Search Procedures

Mauricio G. C. Resende and Celso C. Ribeiro

Ch Chapter 12 Variable Neighborhood Search

Pierre Hansen and Nenad Mladenović

Ch Chapter 13 Very Large-Scale Neighborhood Search

Douglas S. Altner, Ravindra K. Ahuja, Özlem Ergun and James B. Orlin

Ch Chapter 14 Constraint Programming

Eugene C. Freuder and Mark Wallace

Ch Chapter 15 Multi-objective Optimization

Kalyanmoy Deb and Kalyanmoy Deb

Ch Chapter 16 Sharpened and Focused No Free Lunch and Complexity Theory

Darrell Whitley

Ch Chapter 17 Machine Learning

Xin Yao and Yong Liu

Ch Chapter 18 Fuzzy Reasoning

Costas P. Pappis and Constantinos I. Siettos

Ch Chapter 19 Rough-Set-Based Decision Support

Roman Słowiński, Salvatore Greco and Benedetto Matarazzo

Ch Chapter 2 Classical Techniques

Kathryn A. Dowsland

Ch Chapter 20 Hyper-heuristics

Peter Ross

Ch Chapter 21 Approximations and Randomization

Carla P. Gomes and Ryan Williams

Ch Chapter 22 Fitness Landscapes

Colin R. Reeves

Ch Chapter 3 Integer Programming

Robert Bosch and Michael Trick

Ch Chapter 4 Genetic Algorithms

Kumara Sastry, David E. Goldberg and Graham Kendall

Ch Chapter 5 Scatter Search

Manuel Laguna

Ch Chapter 6 Genetic Programming

Riccardo Poli and John Koza

Ch Chapter 7 Artificial Immune Systems

Uwe Aickelin, Dipankar Dasgupta and Feng Gu

Ch Chapter 8 Swarm Intelligence

Daniel Merkle and Martin Middendorf

Ch Chapter 9 Tabu Search

Michel Gendreau and Jean-Yves Potvin

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DOI: 10.1007/978-1-4614-6940-7

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