Metaheuristics

Karl F. Doerner

ISBN 10: 1441944214 / ISBN 13: 9781441944214

Edité par Springer US, Springer US Nov 2010, 2010

A propos de cet article

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 424 pp. Englisch.

N° de réf. du vendeur 9781441944214

Détails bibliographiques

• Titre: Metaheuristics
• Éditeur: Springer US, Springer US Nov 2010
• Date de parution: 2010
• Langue: anglais
• ISBN à 10 chiffres: 1441944214
• ISBN à 13 chiffres: 9781441944214
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 23 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 23 millimètres de profondeur
• Poids: 639 grammes

A propos de ce titre

Synopsis

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.