Electronic Resource

Advances in Bio-inspired Computing for Combinatorial Optimization Problems

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Penilaian

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"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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1408000573	EB0002678	006.3 Pin a	Central Library (OPAC)	Available

Detail Information

Series Title

Intelligent Systems Reference Library

Call Number

006.3 Pin a

Publisher

Berlin Heidelberg : Springer Berlin, Heidelberg., 2013

Collation

x, 188p.: Ill.

Language

English

ISBN/ISSN

978-3-642-40179-4

Classification

006.3

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Natural Computation

Specific Detail Info

-

Statement of Responsibility

RTS

Other version/related

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