ISBN-10:
1461469392
ISBN-13:
9781461469391
Pub. Date:
10/19/2013
Publisher:
Springer US
Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques / Edition 2

Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques / Edition 2

by Edmund K. Burke, Graham Kendall

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Overview

Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques / Edition 2

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.

Product Details

ISBN-13: 9781461469391
Publisher: Springer US
Publication date: 10/19/2013
Edition description: 2nd ed. 2014
Pages: 716
Product dimensions: 6.10(w) x 9.25(h) x 0.06(d)

About the Author

Edmund K. Burke is Deputy Principal for Research at the University of Stirling. His research interests lie at the interface of Operational Research and Computer Science. He is a member of the EPSRC Strategic Advisory Team for Mathematics. He is also a Fellow of the Operational Research Society and the British Computer Society and a member of the UK Computing Research Committee (UKCRC). Professor Burke is Editor-in-chief of the Journal of Scheduling, Area Editor (for Combinatorial Optimisation) of the Journal of Heuristics, Associate Editor of the INFORMS Journal on Computing, Associate Editor of the IEEE Transactions on Evolutionary Computation and a member of the Editorial Board of Memetic Computing. He has edited/authored 14 books and published over 230 refereed papers.

Graham Kendall is the Dunford Professor of Computer Science and a member of the Automated Scheduling, Optimisation and Planning Research Group, School of Computer Science, University of Nottingham, Nottingham, U.K. He is the Deputy Head of the group, which has 9 members of academic staff, about 15 Research Associates/Fellows and about 40 PhD students. He was awarded a BSc (Hons) First Class in Computation from the University of Manchester Institute of Science and Technology (UMIST), UK in 1997 and received his PhD from The University of Nottingham (School of Computer Science) in 2000. He is a Fellow of the Operational Research Society. Professor Kendall’s expertise lies in Operational Research, Meta- and Hyper-Heuristics, Evolutionary Computation and Artificial Intelligence, with a specific interest in scheduling, including timetabling, sports scheduling, cutting and packing and rostering. He has published over 35 refereed journal papers (the vast majority in ISI ranked journals) and over 90 peer reviewed conference papers. He has edited 12 books and authored 10 book chapters.

Table of Contents

Foreword1
Preface3
1Introduction5
2Classical Techniques19
3Integer Programming69
4Genetic Algorithms97
5Genetic Programming127
6Tabu Search165
7Simulated Annealing187
8Variable Neighborhood Search211
9Constraint Programming239
10Multi-Objective Optimization273
11Complexity Theory and the No Free Lunch Theorem317
12Machine Learning341
13Artificial Immune Systems375
14Swarm Intelligence401
15Fuzzy Reasoning437
16Rough Set Based Decision Support475
17Hyper-Heuristics529
18Approximation Algorithms557
19Fitness Landscapes587
Index611

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