Search Methodologies

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.

• Introduction.- Classical Techniques.- Integer Programming.- Genetic Algorithms.- Scatter Search.- Genetic Programming.- Artificial Immune Systems.- Swarm Intelligence.- Tabu Search.- Simulated Annealing.- GRASP: Greedy Randomized Adaptive Search Procedures.- Variable Neighborhood Search.- Very Large-Scale Neighborhood Search.- Constraint Programming.- Multi-objective Optimization.- Sharpened and Focused No Free Lunch and Complexity Theory.- Machine Learning.- Fuzzy Reasoning.- Rough-Set-Based Decision Support.- Hyper-heuristics.- Approximations and Randomization.- Fitness Landscapes.

REVIEW EXCERPTS OF FIRST EDTION: "This edited book is ... designed to provide introductions to topics in search methodology. ... The chapters are well-written, accurate and carefully presented and provide a good exposition of each of the topics. ... Although aimed at PhD students, and I would certainly recommend the book to them and to supervisors, this volume should prove very useful to a wider audience ... . It provides an excellent introduction to a large set of techniques in search methodology and is a pleasure to read." (JM Wilson, Journal of the Operational Research Society, Vol. 58 (3), 2007)