Towards a Better Understanding of the Local Attractor in Particle Swarm Optimization: Speed and Solution Quality

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Lange V, Schmitt M, Wanka R
Title edited volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher: Springer Verlag
Publication year: 2014
Conference Proceedings Title: Proc. International Conference on Adaptive and Intelligent Systems (ICAIS)
Pages range: 90-99
ISSN: 1611-3349
Language: English


Abstract


Particle Swarm Optimization (PSO) is a popular nature-inspired meta-heuristic for solving continuous optimization problems. Although this technique is widely used, the understanding of the mechanisms that make swarms so successful is still limited. We present the first substantial experimental investigation of the influence of the local attractor on the quality of exploration and exploitation. We compare in detail classical PSO with the social-only variant where local attractors are ignored. To measure the exploration capabilities, we determine how frequently both variants return results in the neighborhood of the global optimum. We measure the quality of exploitation by considering only function values from runs that reached a search point sufficiently close to the global optimum and then comparing in how many digits such values still deviate from the global minimum value. It turns out that the local attractor significantly improves the exploration, but sometimes reduces the quality of the exploitation. The effects mentioned can also be observed by measuring the potential of the swarm. © 2014 Springer International Publishing Switzerland.



FAU Authors / FAU Editors

Lange, Vanessa
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)
Schmitt, Manuel
Professur für Informatik (Effiziente Algorithmen und Kombinatorische Optimierung)
Wanka, Rolf Prof. Dr.
Professur für Informatik (Effiziente Algorithmen und Kombinatorische Optimierung)


How to cite

APA:
Lange, V., Schmitt, M., & Wanka, R. (2014). Towards a Better Understanding of the Local Attractor in Particle Swarm Optimization: Speed and Solution Quality. In Proc. International Conference on Adaptive and Intelligent Systems (ICAIS) (pp. 90-99). Bournemouth, UK: Springer Verlag.

MLA:
Lange, Vanessa, Manuel Schmitt, and Rolf Wanka. "Towards a Better Understanding of the Local Attractor in Particle Swarm Optimization: Speed and Solution Quality." Proceedings of the International Conference on Adaptive and Intelligent Systems (ICAIS), Bournemouth, UK Springer Verlag, 2014. 90-99.

BibTeX: 

Last updated on 2018-19-04 at 02:53