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Produktbild: An Introduction to Metaheuristics for Optimization

An Introduction to Metaheuristics for Optimization

Aus der Reihe Natural Computing Series

54,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational...

Beschreibung

The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies.


This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

Rezension

“I would recommend this book for students in the area of operations research, but also for students and professionals from other fields (like natural sciences or social sciences) who would like not only to apply metaheuristics to solve the problems … but also to understand how they work.” (Marcin Anholcer, zbMATH 1427.90001, 2020)

Produktdetails

Einband

Gebundene Ausgabe
Erscheinungsdatum

13.11.2018
Abbildungen

XII, 226 p. 44 illus. in color.
Verlag Springer

Produktdetails

Einband

Gebundene Ausgabe
Erscheinungsdatum

13.11.2018
Abbildungen

XII, 226 p. 44 illus. in color.
Verlag Springer
Seitenzahl

226
Maße (L/B/H)

24,1/16/1,9 cm
Gewicht

478 g
Sprache

Englisch
ISBN

978-3-319-93072-5
Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: An Introduction to Metaheuristics for Optimization

  • Problems, Algorithms, Computational Complexity.- Search Space.- Tabu Search.- Simulated Annealing.- Ant Colony Optimization (ACO).- Non-PSO Optimization.- Firefly Algorithm, Cuckoo Algorithm, Lévy Flights.- Evolutionary Algorithms: Foundations.- Evolutionary Algorithms: Advanced.- Phase Transition in Optimization Problems.- Performance and Limitations of Metaheuristics.- Statistical Analysis of Research Spaces.