Particle Swarm Optimization in High-Dimensional Bounded Search Spaces

Conference contribution


Publication Details

Author(s): Helwig S, Wanka R
Title edited volumes: Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 2007
Publication year: 2007
Conference Proceedings Title: Proceedings of the 2007 IEEE Swarm Intelligence Symposium
Pages range: 198-205


Abstract


When applying Particle Swarm Optimization (PSO) to real world optimization problems, often boundary constraints have to be taken into account. In this paper, we will show that the bound handling mechanism essentially influences the swarm behavior, especially in high-dimensional search spaces. In our theoretical analysis, we will prove that all particles are initialized very close to the boundary with overwhelming probability, and that the global guide is expected to leave the search space in every forth dimension. Afterwards, we investigate the initialization process when optimizing the Sphere function, a widely used benchmark, in more detail in order to provide a first step towards explaining previously observed phenomena. Moreover, we will present a broad experimental study of commonly applied bound handling mechanisms on a variety of benchmark functions which is useful for choosing an appropriate strategy in real world applications. Finally, we will derive some guidelines for the practical application of the PSO algorithm in high-dimensional bounded search spaces. © 2007 IEEE.



FAU Authors / FAU Editors

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


How to cite

APA:
Helwig, S., & Wanka, R. (2007). Particle Swarm Optimization in High-Dimensional Bounded Search Spaces. In Proceedings of the 2007 IEEE Swarm Intelligence Symposium (pp. 198-205). Honolulu, Hawaii, US.

MLA:
Helwig, Sabine, and Rolf Wanka. "Particle Swarm Optimization in High-Dimensional Bounded Search Spaces." Proceedings of the IEEE Swarm Intelligence Symposium 2007, Honolulu, Hawaii 2007. 198-205.

BibTeX: 

Last updated on 2018-20-10 at 04:40