Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Evolution of Forces for Particle Swarm Optimisation using Genetic Programming
  • Publication Type:
  • Authors:
    Chio CD, Poli R, Langdon WB
  • Publication date:
  • Published proceedings:
  • Notes:
    Rejected keywords: genetic algorithms, genetic programming, PSO notes:
Particle Swarm Optimisation (PSO) uses a population of interacting particles that, controlled by physical forces, fly over the fitness landscape searching for an optimal solution. We extend our previous research on evolving these forces by considering additional ingredients, such as the velocity of the neighbourhood best and time, and different neighbourhood topologies, namely the global and ring ones. We test the evolved extended PSOs (XPSOs) on various classes of benchmark problems. We show that evolutionary computation (and in particular genetic programming, GP) can automatically generate new PSO algorithms that outperform standard PSOs designed by people as well as some previously evolved ones.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Dept of Computer Science
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by