Advances in Bio-inspired Computing for Combinatorial Optimization Problems

  • Camelia-Mihaela¬†Pintea

Part of the Intelligent Systems Reference Library book series (ISRL, volume 57)

Table of contents

  1. Front Matter
    Pages 1-8
  2. Biological Computing and Optimization

    1. Front Matter
      Pages 1-1
    2. Camelia-Mihaela Pintea
      Pages 3-19
    3. Camelia-Mihaela Pintea
      Pages 21-28
  3. Ant Algorithms

    1. Front Matter
      Pages 29-29
    2. Camelia-Mihaela Pintea
      Pages 31-55
    3. Camelia-Mihaela Pintea
      Pages 57-80
    4. Camelia-Mihaela Pintea
      Pages 81-104
  4. Bio-inspired Multi-agent Systems

    1. Front Matter
      Pages 105-105
    2. Camelia-Mihaela Pintea
      Pages 107-122
  5. Applications with Bio-inspired Algorithms

    1. Front Matter
      Pages 123-123
    2. Camelia-Mihaela Pintea
      Pages 125-141
    3. Camelia-Mihaela Pintea
      Pages 143-161
  6. Conclusions and Remarks

    1. Front Matter
      Pages 163-163
    2. Camelia-Mihaela Pintea
      Pages 165-170
  7. Back Matter
    Pages 171-188

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.


Artificial Intelligence Combinatorial Optimization Intelligent Systems Metaheuristics Multi-agent Systems Natural Computing Pattern Recognition

Authors and affiliations

  • Camelia-Mihaela¬†Pintea
    • 1
  1. 1.Technical UniversityCluj-NapocaRomania

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2014
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-40178-7
  • Online ISBN 978-3-642-40179-4
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • About this book