Particle Swarms: The Second Decade

Call for Papers

The particle swarm is a remarkable optimizer that has evolved in the last decade since it was proposed. It is little understood, yet it has a very simple formulation.

The special issue will focus on recent advances in PSO, both in terms of the understanding and the applications of the algorithm.

The aim is to attract papers on particularly innovative research, speculative ideas, and novel applications that could act as seeds for PSO research in its second decade.

PSOs have always been studied under the umbrella of genetic and evolutionary computation. Their presence in conferences and journals in this field has exponentially increased in the last decade. So, we believe this special issue will be of considerable interest for the readership of the journal.

Topics include (but are not limited to):

  • Novel empirical and theoretical analyses of PSO population dynamics
  • Innovative studies and algorithms for setting PSO parameters
  • New adaptive and parameterless PSO
  • Analyses and new proposals of social network topologies
  • PSO for combinatorial and hierarchical search spaces
  • Novel PSOs for dynamic problems, noisy functions, and multimodal functions
  • Advanced bare-bones/distribution-based PSOs
  • Unconventional hybrids of PSO with other techniques
  • Novel applications in engineering, biomedicine, clustering, classification, entertainment, finance, image and signal processing, graphics, computational intelligence, and robotics

Authors should follow the Journal of Artificial Evolution and Applications manuscript format described at the journal site http://www.hindawi.com/journals/jaea/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/, according to the following timetable:

Manuscript Due July 20, 2007
First Round of Reviews November 1, 2007
Publication Date February 1, 2008

Guest Editors

  • Riccardo Poli, Department of Computer Science, University of Essex, Colchester CO4 3SQ, UK
  • Jim Kennedy, US Bureau of Labor Statistics, Washington, DC 20212 0001, USA
  • Tim Blackwell, Department of Computing, Goldsmiths College, University of London, London SE14 6NW, UK
  • Alex Freitas, Computing Laboratory, The University of Kent, Canterbuy, Kent CT2 7NZ, UK