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Advances in Bio-inspired Computing for Combinatorial Optimization Problems

  • Kartonierter Einband
  • 188 Seiten
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This book illustrates recent bio-inspired efficient algorithms for solving NP-hard problems. Discusses theoretical bio-inspired co... Weiterlesen
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Beschreibung

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.

"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.

Inhalt

Part I Biological Computing and Optimization.- Part II Ant Algorithms.- Part III Bio-inspired Multi-Agent Systems.- Part IV Applications with Bio-inspired Algorithms.- Part V Conclusions and Remarks.

Produktinformationen

Titel: Advances in Bio-inspired Computing for Combinatorial Optimization Problems
Autor:
EAN: 9783642438776
ISBN: 978-3-642-43877-6
Format: Kartonierter Einband
Genre: Technik
Anzahl Seiten: 188
Gewicht: 314g
Größe: H235mm x B235mm x T155mm
Jahr: 2015
Auflage: Softcover reprint of the original 1st ed. 2014

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