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An Introduction to Metaheuristics for Optimization de Bastien Chopard

An Introduction to Metaheuristics for Optimization: Natural Computing Series

Autor Bastien Chopard, Marco Tomassini
en Limba Engleză Hardback – 13 noi 2018
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.
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Specificații

ISBN-13: 9783319930725
ISBN-10: 3319930729
Pagini: 226
Ilustrații: XII, 226 p. 44 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.51 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Natural Computing Series

Locul publicării:Cham, Switzerland

Cuprins

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.

Recenzii

“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)

Notă biografică

Bastien Chopard is a professor in the Département d'informatique of the Université de Genève, where he directs the Scientific and Parallel Computing Group. His main research activity concerns the study of complex systems, in particular the development of new numerical methods to model and simulate phenomena in natural sciences, economics, social systems, and biomedical applications, the key tools used being cellular automata, the lattice Boltzmann method, and multiagent techniques. 
Marco Tomassini is an honorary professor at the Faculty of Business and Economics of the University of Lausanne (HEC). After obtaining a PhD degree in Theoretical Chemistry working on computer simulations of condensed matter systems, he switched to Computer Science and complex systems investigations. His main research activities have since focused on parallel computing, cellular automata, evolutionary algorithms, the structure of difficult problem landscapes, complex networks, and evolutionary games.

Textul de pe ultima copertă

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.

Caracteristici

Accessible introduction, suitable for students and for self-study Assumes basic computing skills only as a prerequisite Authors are interdisciplinary researchers, and they bring this into their approach