Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Ke-Lin Du, PhD, is Affiliate Associate Professor at Concordia University, Montreal, Quebec, Canada, and Founder and CEO of Xonlink Inc, Ningbo, China.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 28,88 per la spedizione da Regno Unito a U.S.A.
Destinazione, tempi e costiEUR 23,00 per la spedizione da Germania a U.S.A.
Destinazione, tempi e costiDa: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 includesdetailed 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 Metaheuristicsis 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. 456 pp. Englisch. Codice articolo 9783319411910
Quantità: 2 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 452. Codice articolo 26374883714
Quantità: 4 disponibili
Da: moluna, Greven, Germania
Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers a comprehensive and state-of-the-art introduction to nature-inspired metaheuristicsIncludes detailed, implementable algorithmic flowcharts for the most popular algorithmsDiscusses over 100 diff. Codice articolo 122061266
Quantità: Più di 20 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. 452. Codice articolo 372243037
Quantità: 4 disponibili
Da: Mispah books, Redhill, SURRE, Regno Unito
Hardcover. Condizione: Like New. Like New. book. Codice articolo ERICA79033194119186
Quantità: 1 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND pp. 452. Codice articolo 18374883720
Quantità: 4 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Buch. Condizione: Neu. Neuware -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.Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 456 pp. Englisch. Codice articolo 9783319411910
Quantità: 2 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 includesdetailed 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 Metaheuristicsis 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. Codice articolo 9783319411910
Quantità: 1 disponibili