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A Peek into the Swarm: Analysis of the Gravitational Search Algorithm and Recommendations for Parameter Selection

  • 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.

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Metadaten
Author:Florian Knauf, Ralf BrunsGND
URN:urn:nbn:de:bsz:960-opus4-15078
DOI original:https://doi.org/10.1145/3321707.3321774
ISBN:978-1-4503-6111-8
Parent Title (English):GECCO'19: Proceedings of the 2019 Genetic and Evolutionary Computation Conference, Prague, Czech Republic — July 13 - 17, 2019
Publisher:The Assiciation for Computing Machinery (ACM)
Place of publication:New York
Document Type:Conference Proceeding
Language:English
Year of Completion:2019
Release Date:2019/11/07
Tag:Swarm Intelligence
GND Keyword:Schwarmintelligenz
First Page:30
Last Page:38
Note:
The source code for the experiments in this paper can be found at https://github.com/fknauf/gsa-a-peek-into-the-swarm .
Institutes:Fakultät IV - Wirtschaft und Informatik
DDC classes:004 Informatik
Licence (German):License LogoUrheberrechtlich geschützt