Multiswarms, exclusion, and anti-convergence in dynamic environments

  title={Multiswarms, exclusion, and anti-convergence in dynamic environments},
  author={Tim Blackwell and Juergen Branke},
  journal={IEEE Transactions on Evolutionary Computation},
Many real-world problems are dynamic, requiring an optimization algorithm which is able to continuously track a changing optimum over time. In this paper, we explore new variants of particle swarm optimization (PSO) specifically designed to work well in dynamic environments. The main idea is to split the population of particles into a set of interacting swarms. These swarms interact locally by an exclusion parameter and globally through a new anti-convergence operator. In addition, each swarm… CONTINUE READING
Highly Influential
This paper has highly influenced 77 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 460 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 234 extracted citations

460 Citations

Citations per Year
Semantic Scholar estimates that this publication has 460 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 38 references

Particle swarms and population diversity

  • Soft Computing, vol. 9, no. 11, pp. 793–802, 2005…
  • 2005
Highly Influential
9 Excerpts

Adaptive particle swarm optimization: Detection and response to dynamic systems

  • X. Hu, R. Eberhart
  • Proc. Congr. Evol. Comput., 2002, pp. 1666–1670.
  • 2002
Highly Influential
9 Excerpts

Similar Papers

Loading similar papers…