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Metaheuristics: Outlines, MATLAB Codes and Examples de Ali Kaveh

Metaheuristics: Outlines, MATLAB Codes and Examples

Autor Ali Kaveh, Taha Bakhshpoori
en Limba Engleză Hardback – 7 apr 2019
The book presents eight well-known and often used algorithms besides nine newly developed algorithms by the first author and his students in a practical implementation framework.
Matlab codes and some benchmark structural optimization problems are provided. The aim is to provide an efficient context for experienced researchers or readers not familiar with theory, applications and computational developments of the considered metaheuristics.
The information will also be of interest to readers interested in application of metaheuristics for hard optimization, comparing conceptually different metaheuristics and designing new metaheuristics.
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Specificații

ISBN-13: 9783030040666
ISBN-10: 3030040666
Pagini: 162
Ilustrații: XII, 190 p. 116 illus., 112 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.46 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland

Cuprins

Introduction.- Preliminaries and frameworks.- Artificial bee colony algorithm.- Big bang big crunch algorithm.- Teaching Learning Based Optimization Algorithm.- Imperialist Competitive Algorithm.- Cuckoo search.- Charged system search Algorithm.- Ray Optimization Algorithm.- Colliding Bodies Optimization Algorithm.- Tug-of-war optimization Algorithm.- Water Evaporation Optimization Algorithm.- Vibrating particles system algorithm.- Cyclical parthenogenesis algorithm.- Thermal exchange optimizaton algorithm.

Textul de pe ultima copertă

The book presents eight well-known and often used algorithms besides nine newly developed algorithms by the first author and his students in a practical implementation framework.
Matlab codes and some benchmark structural optimization problems are provided. The aim is to provide an efficient context for experienced researchers or readers not familiar with theory, applications and computational developments of the considered metaheuristics.
The information will also be of interest to readers interested in application of metaheuristics for hard optimization, comparing conceptually different metaheuristics and designing new metaheuristics.

Caracteristici

Provides easy to understand information on the novel and efficient metaheuristics developed by the authors
Useful for transformation of the algorithms from theory to practice for global optimization problems
Includes Matlab codes and benckmark structural optimization problems and their solutions