Particle Swarm Optimization with Velocity Adaptation

Conference contribution


Publication Details

Author(s): Helwig S, Neumann F, Wanka R
Title edited volumes: Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009
Publication year: 2009
Conference Proceedings Title: Proc. 2009 International Conference on Adaptive and Intelligent Systems
Pages range: 146-151


Abstract


Particle swarm optimization (PSO) algorithms have gained increasing interest for dealing with continuous optimization problems in recent years. Often such problems involve boundary constraints. In this case, one has to cope with the situation that particles may leave the feasible search space. To deal with such situations different bound handling methods have been proposed in the literature and it has been observed that the success of PSO algorithms depends on a large degree on the used bound handling method. In this paper, we propose an alternative approach to cope with bounded search spaces. The idea is to introduce a velocity adaptation mechanism into PSO algorithms that is similar to step size adaptation used in evolution strategies. Using this approach we show that the bound handling method becomes less important for PSO algorithms and that using velocity adaptation leads to better results for a wide range of benchmark functions. © 2009 IEEE.


FAU Authors / FAU Editors

Wanka, Rolf Prof. Dr.
Professur für Informatik (Effiziente Algorithmen und Kombinatorische Optimierung)


How to cite

APA:
Helwig, S., Neumann, F., & Wanka, R. (2009). Particle Swarm Optimization with Velocity Adaptation. In Proc. 2009 International Conference on Adaptive and Intelligent Systems (pp. 146-151). Klagenfurt, Austria, AT.

MLA:
Helwig, Sabine, Frank Neumann, and Rolf Wanka. "Particle Swarm Optimization with Velocity Adaptation." Proceedings of the International Conference on Adaptive and Intelligent Systems (ICAIS'09), Klagenfurt, Austria 2009. 146-151.

BibTeX: 

Last updated on 2018-28-09 at 13:03