New Advancements In Swarm Algorithms
Cuevas Erik
Venduto da Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Venditore AbeBooks dal 27 febbraio 2001
Nuovi - Rilegato
Condizione: Nuovo
Quantità: 15 disponibili
Aggiungere al carrelloVenduto da Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Venditore AbeBooks dal 27 febbraio 2001
Condizione: Nuovo
Quantità: 15 disponibili
Aggiungere al carrelloCodice articolo V9783030163389
This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineers and practitioners solve their own optimization problems.
This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineers and practitioners solve their own optimization problems.
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