By Topic

Convergence Analysis of PSO Inspired by r- and K-Selection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yunyi Yan ; ICIE Inst. of Electromech. Eng. Sch., Xidian Univ., Xian ; Baolong Guo

As a novel particles swarm optimization algorithm, r/KPSO takes the advantages of r-selection and K selection. Particles in high fitness (K-subswarm called in this paper) perform K-selection. K-subswarm only can produce few progenies but the progenies are nurtured delicately with much parent care. On the other hand, r-selection is performed for other particles in relatively low fitness (r-subswarm called). r-subswarm can produce a large number of progenies with little parent care and the progenies have to compete for survival according to fitness and only the best ones can survive. In r/KPSO, the particles performed r-selection mainly explore the search space as possible as they can to find more potential solutions in large speed, and those particles performed K-selection keep the current optimum solutions and exploit the space as they can to find more ideal solutions. To evaluate convergence speed quantitatively, a novel criterion named first converging generation (FCG) is introduced. Experiments were conducted on standard benchmark functions, and experimental results showed r/KPSO could converge in higher speed in terms of FCG and in higher precision than standard PSO (SPSO).

Published in:

Intelligent Systems Design and Applications, 2008. ISDA '08. Eighth International Conference on  (Volume:2 )

Date of Conference:

26-28 Nov. 2008