Authors:
- 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
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 57)
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Table of contents (9 chapters)
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Front Matter
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Biological Computing and Optimization
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Front Matter
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Ant Algorithms
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Front Matter
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Bio-inspired Multi-agent Systems
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Front Matter
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Applications with Bio-inspired Algorithms
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Front Matter
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Conclusions and Remarks
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Front Matter
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Back Matter
About this book
"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.
Authors and Affiliations
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Technical University, Cluj-Napoca, Romania
Camelia-Mihaela Pintea
Bibliographic Information
Book Title: Advances in Bio-inspired Computing for Combinatorial Optimization Problems
Authors: Camelia-Mihaela Pintea
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-642-40179-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2014
Hardcover ISBN: 978-3-642-40178-7Published: 20 August 2013
Softcover ISBN: 978-3-642-43877-6Published: 21 August 2015
eBook ISBN: 978-3-642-40179-4Published: 13 August 2013
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: X, 188
Topics: Computational Intelligence, Artificial Intelligence, Operations Research/Decision Theory