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Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

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  • © 2009

Overview

Editors:
  1. Natalio Krasnogor

    1. School of Computer Sciences and Information Technology, University of Nottingham, Nottingham, UK

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  2. María Belén Melián-Batista

    1. Universidad de La Laguna, Spain

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  3. José Andrés Moreno Pérez

    1. DEIOC, Facultad de Matemáticas, Universidad de La Laguna, La Laguna, Spain

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  4. J. Marcos Moreno-Vega

    1. DEIOC, Facultad de Matemáticas, Universidad de La Laguna, La Laguna, Spain

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  5. David Alejandro Pelta

    1. Department of Computer Science and Artificial Intelligence, E.T.S.I Informática y de Telecomunicación, University of Granada, Granada, Spain

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  • Presents latest results in nature inspired cooperative strategies for optimization

Part of the book series: Studies in Computational Intelligence (SCI, volume 236)

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Table of contents (24 chapters)

  1. Front Matter

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  2. Exploration in Stochastic Algorithms: An Application on \(\cal M\!AX\!\)–\(\cal MI\!N\!\) Ant System

    • Paola Pellegrini, Daniela Favaretto, Elena Moretti
    Pages 1-13

  3. Sensitive Ants: Inducing Diversity in the Colony

    • C. -M. Pintea, C. Chira, D. Dumitrescu
    Pages 15-24

  4. Decentralised Communication and Connectivity in Ant Trail Networks

    • Duncan E. Jackson, Mesude Bicak, Mike Holcombe
    Pages 25-36

  5. Detection of Non-structured Roads Using Visible and Infrared Images and an Ant Colony Optimization Algorithm

    • Rafael Arnay, Leopoldo Acosta, Marta Sigut, Jonay T. Toledo
    Pages 37-47

  6. A Nature Inspired Approach for the Uncapacitated Plant Cycle Location Problem

    • Belén Melián-Batista, J. Marcos Moreno-Vega, Nitesh Vaswani, Rayco Yumar
    Pages 49-60

  7. Particle Swarm Topologies for Resource Constrained Project Scheduling

    • Jens Czogalla, Andreas Fink
    Pages 61-73

  8. Discrete Particle Swarm Optimization Algorithm for Data Clustering

    • R. Karthi, S. Arumugam, K. Ramesh Kumar
    Pages 75-88

  9. A Simple Distributed Particle Swarm Optimization for Dynamic and Noisy Environments

    • Xiaohui Cui, Jesse St. Charles, Thomas E. Potok
    Pages 89-102

  10. Exploring Feasible and Infeasible Regions in the Vehicle Routing Problem with Time Windows Using a Multi-objective Particle Swarm Optimization Approach

    • Juan P. Castro, Dario Landa-Silva, José A. Moreno Pérez
    Pages 103-114

  11. Two-Swarm PSO for Competitive Location Problems

    • Clara M. Campos Rodríguez, José A. Moreno Pérez, Hartmut Noltemeier, Dolores R. Santos Peñate
    Pages 115-126

  12. Aerodynamic Wing Optimisation Using SOMA Evolutionary Algorithm

    • Miroslav Červenka, Vojtěch Křesálek
    Pages 127-138

  13. Experimental Analysis of a Variable Size Mono-population Cooperative-Coevolution Strategy

    • Olivier Barrière, Evelyne Lutton
    Pages 139-152

  14. Genetic Algorithm for Tardiness Minimization in Flowshop with Blocking

    • Tiago de O. Januario, José Elias C. Arroyo, Mayron César O. Moreira
    Pages 153-164

  15. Landscape Mapping by Multi-population Genetic Algorithm

    • Yuebin B. Guo, Kwok Yip Szeto
    Pages 165-176

  16. An Interactive Simulated Annealing Multi-agents Platform to Solve Hierarchical Scheduling Problems with Goals

    • Souhail Dhouib, Sana Kouraïchi, Taïcir loukil, Habib Chabchoub
    Pages 177-187

  17. Genetic Algorithm and Advanced Tournament Selection Concept

    • Radomil Matoušek
    Pages 189-196

  18. Terrain-Based Memetic Algorithms for Vector Quantizer Design

    • Carlos R. B. Azevedo, Flávia E. A. G. Azevedo, Waslon T. A. Lopes, Francisco Madeiro
    Pages 197-211

  19. Cooperating Classifiers

    • Magnus Jändel
    Pages 213-225

  20. Evolutionary Multimodal Optimization for Nash Equilibria Detection

    • Rodica Ioana Lung, Dan Dumitrescu
    Pages 227-237
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Keywords

About this book

The inspiration from Biology and the Natural Evolution process has become a research area within computer science. For instance, the description of the arti?cial neuron given by McCulloch and Pitts was inspired from biological observations of neural mechanisms; the power of evolution in nature in the diverse species that make up our world has been related to a particular form of problem solving based on the idea of survival of the ?ttest; similarly, - ti?cial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The ?rst and second editions of the International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), were held in Granada, Spain, 2006, and in Acireale, Italy, 2007, respectively. As in these two previous editions, the aim of NICSO 2008, held in Tenerife, Spain, was to provide a forum were the latest ideas and state of the art research related to nature inspired cooperative strategies for problem solving were discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributionsincludenature-inspiredtechniqueslikeGeneticAlgorithms,Ant Colonies, Amorphous Computing, Arti?cial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

Editors and Affiliations

  • School of Computer Sciences and Information Technology, University of Nottingham, Nottingham, UK

    Natalio Krasnogor

  • Universidad de La Laguna, Spain

    María Belén Melián-Batista

  • DEIOC, Facultad de Matemáticas, Universidad de La Laguna, La Laguna, Spain

    José Andrés Moreno Pérez, J. Marcos Moreno-Vega

  • Department of Computer Science and Artificial Intelligence, E.T.S.I Informática y de Telecomunicación, University of Granada, Granada, Spain

    David Alejandro Pelta

Bibliographic Information

  • Book Title: Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

  • Editors: Natalio Krasnogor, María Belén Melián-Batista, José Andrés Moreno Pérez, J. Marcos Moreno-Vega, David Alejandro Pelta

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-03211-0

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2009

  • Hardcover ISBN: 978-3-642-03210-3Published: 14 September 2009

  • Softcover ISBN: 978-3-642-26034-6Published: 04 May 2012

  • eBook ISBN: 978-3-642-03211-0Published: 04 October 2009

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XXVIII, 300

  • Topics: Engineering Design, Artificial Intelligence, Robotics and Automation, Mathematical and Computational Engineering

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