Metaheuristics: Progress in Complex Systems Optimization

Doerner, Karl F. (Editor)/ Gendreau, Michel (Editor)/ Greistorfer, Peter (Editor)/ Gutjahr, Walter (Editor)/ Hartl, Richard F. (Editor)

ISBN 10: 0387719199 / ISBN 13: 9780387719191

Verlag: Springer Verlag, 2007

Beschreibung

1st edition. 408 pages. 9.25x6.25x1.00 inches. In Stock.

Bestandsnummer des Verkäufers x-0387719199

Bibliografische Details

• Titel: Metaheuristics: Progress in Complex Systems Optimization
• Verlag: Springer Verlag
• Erscheinungsjahr: 2007
• Sprache: Englisch
• ISBN-10: 0387719199
• ISBN-13: 9780387719191
• Einband: Hardcover
• Zustand: Brand New

Über diesen Titel

Inhaltsangabe

This book's aim is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

Von der hinteren Coverseite

The aim of METAHEURISTICS: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

Highlighted are recent developments in the areas of Simulated Annealing, Path Relinking, Scatter Search, Tabu Search, Variable Neighborhood Search, Hyper-heuristics, Constraint Programming, Iterated Local Search, GRASP, bio-inspired algorithms like Genetic Algorithms, Memetic Algorithms, Ant Colony Optimization or Swarm Intelligence, and several other paradigms.