This book illustrates recent bio-inspired efficient algorithms for solving NP-hard problems. Discusses theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots, variations of the Traveling Salesman Problem and more.
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Destinations, frais et délaisVendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar3113020226072
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Vendeur : Buchpark, Trebbin, Allemagne
Etat : Sehr gut. Zustand: Sehr gut - Buchschnitt verkürzt- gepflegter, sauberer Zustand - Ausgabejahr 2014 | Seiten: 200 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 24111768/12
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive ants; virtual sensitive robots; ant-based techniques for static and dynamic routing problems; stigmergic collaborative agents and learning sensitive agents.This monograph is useful for researchers, students and all people interested in the recent natural computing frameworks. The reader is presumed to have knowledge of combinatorial optimization, graph theory, algorithms and programming. The book should furthermore allow readers to acquire ideas, concepts and models to use and develop new software for solving complex real-life problems. 200 pp. Englisch. N° de réf. du vendeur 9783642401787
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783642401787_new
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Hardcover. Etat : Neu. Neu Neuware, auf Lager - 'Advances in Bio-inspired Combinatorial Optimization Problems' illustrates several recent bio-inspired efficient algorithms for solving NP-hard problems.Theoretical bio-inspired concepts and models, in particular for agents, ants and virtual robots are described. Large-scale optimization problems, for example: the Generalized Traveling Salesman Problem and the Railway Traveling Salesman Problem, are solved and their results are discussed.Some of the main concepts and models described in this book are: inner rule to guide ant search - a recent model in ant optimization, heterogeneous sensitive ants; virtual sensitive robots; ant-based techniques for static and dynamic routing problems; stigmergic collaborative agents and learning sensitive agents.This monograph is useful for researchers, students and all people interested in the recent natural computing frameworks. The reader is presumed to have knowledge of combinatorial optimization, graph theory, algorithms and programming. The book should furthermore allow readers to acquire ideas, concepts and models to use and develop new software for solving complex real-life problems. N° de réf. du vendeur INF1000764065
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces new bio-inspired techniques based on ants, agents and virtual robots Solves real-life complex problems using the introduced bio-inspired techniques Recent research on Bio-inspired Computing for Combinatorial Optimization Problems. N° de réf. du vendeur 5059550
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Hardcover. Etat : Brand New. 2014 edition. 200 pages. 9.25x6.50x0.75 inches. In Stock. N° de réf. du vendeur x-3642401783
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Hardcover. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA77336424017836
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