TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Knauf, Florian
A1  - Bruns, Ralf
T1  - A Peek into the Swarm: Analysis of the Gravitational Search Algorithm and Recommendations for Parameter Selection
T2  - GECCO'19: Proceedings of the 2019 Genetic and Evolutionary Computation Conference, Prague, Czech Republic — July 13 - 17, 2019
N2  - The Gravitational Search Algorithm is a swarm-based optimization metaheuristic that has been successfully applied to many problems. However, to date little analytical work has been done on this topic.

This paper performs a mathematical analysis of the formulae underlying the Gravitational Search Algorithm. From this analysis, it derives key properties of the algorithm's expected behavior and recommendations for parameter selection. It then confirms through empirical examination that these recommendations are sound.
KW  - Swarm Intelligence
KW  - Schwarmintelligenz
Y1  - 2019
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:960-opus4-15078
SN  - 978-1-4503-6111-8
SB  - 978-1-4503-6111-8
U6  - https://doi.org/10.25968/opus-1507
DO  - https://doi.org/10.25968/opus-1507
N1  - The source code for the experiments in this paper can be found at https://github.com/fknauf/gsa-a-peek-into-the-swarm .
SP  - 30
EP  - 38
PB  - The Assiciation for Computing Machinery (ACM)
CY  - New York
ER  -