Search Methodologies

Introductory Tutorials in Optimization and Decision Support Techniques

Edmund K. Burke, Graham Kendall

632 pages, parution le 12/12/2005

Ajouter à une liste

Indisponible

Résumé

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 18 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.

Topical chapters in the book are highlighted in the contents. 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.

Written for: PhD students, final year undergraduates and researchers in the optimization/search domain, including OR, Artificial Intelligence, Engineering, Management and Business; practitioners developing optimization/search systems

L'auteur - Graham Kendall

G. Kendall , University of Nottingham, Nottingham, UK

Sommaire

Introduction; Edmund Burke and Graham Kendall
Classical Techniques; Kathryn Dowsland
Integer Programming; Bob Bosch and Michael Trick
Genetic Algorithms; Kumara Sastry, David Goldberg, and Graham Kendall
Genetic Programming; John Koza and Riccardo Poli
Tabu Search; Michael Gendreau and Jean-Yves Potvin
Simulated Annealing; Emile Aarts, Jan Korst and Wil Michiels
Variable Neighborhood Search; Pierre Hansen and Nenad Mladenovic
Constraint Programming; Eugene Freuder and Mark Wallace
Multi-Objective Optimization; Kalyanmoy Deb
Complexity Theory and The No Free Lunch Theorem; Darrell Whitley and Jean Paul Watson
Machine Learning; Xin Yao and Yong Liu
Artificial Immune Systems; Uwe Aickelin and Dipankar Dasgupta
Swarm Intelligence; Daniel Merkle and Martin Middendorf
Fuzzy Reasoning; Costas Pappis and Constantinos Siettos
Rough Set Based Decision Support; Roman Slowinski, Salvatore Greco and Benedetto Matarazzo
Hyper-heuristics; Peter Ross
Approximation Algorithms; Carla Gomes and Ryan Williams
Fitness Landscapes; Colin Reeves

Voir tout

Replier

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Edmund K. Burke, Graham Kendall
Parution	12/12/2005
Nb. de pages	632
Format	16 x 24
Couverture	Relié
Poids	990g
Intérieur	Noir et Blanc
EAN13	9780387234601
ISBN13	978-0-387-23460-1