Search and Optimization by Metaheuristics: Techniques and Algorithms Inspired by Nature - Softcover

Du, Ke-Lin; Swamy, M. N. S.

 
9783319822907: Search and Optimization by Metaheuristics: Techniques and Algorithms Inspired by Nature
Softcover
ISBN 10: 331982290X ISBN 13: 9783319822907
Verlag: Birkhäuser, 2018

Inhaltsangabe

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing.  Over 100 different types of these methods are discussed in detail.  The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones.  

An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material.  Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others.  General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described.  Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics.  Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. 

Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science.  It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

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Über die Autorin bzw. den Autor

Ke-Lin Du, PhD, is Affiliate Associate Professor at Concordia University, Montreal, Quebec, Canada, and Founder and CEO of Xonlink Inc, Ningbo, China.


M.N.S. Swamy, PhD, is Research Professor and Tier I Concordia Research Chair in the Department of Electrical and Computer Engineering at Concordia University, Montreal, Quebec, Canada.

Von der hinteren Coverseite

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing.  Over 100 different types of these methods are discussed in detail.  The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones.  

An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material.  Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others.  General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described.  Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics.  Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. 

Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science.  It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

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Verlag
Birkhäuser
Erscheinungsdatum
2018
Sprache
Englisch
ISBN 10 
331982290X
ISBN 13 
9783319822907
Einband
Taschenbuch
Anzahl der Seiten
456
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