Journal
DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE
Volume 620, Issue -, Pages 270-277Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-62410-5_33
Keywords
Gravitational search algorithm; Particle Swarm Optimization
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Funding
- ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness)
- National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) [FCOMP - 01-0124-FEDER-022701]
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The gravitational search algorithm (GSA) is reviewed, by presenting a tutorial analysis of its key issues. As any other metaheuristic, GSA requires the selection of some heuristic parameters. One parameter which is crucial in regulating the exploratory capabilities of this algorithm is the gravitational constant. An analysis regarding this parameter selection is presented and a heuristic rule proposed for this purpose. The GSA performance is compared both with a hybridization with particle swarm optimization (PSO) and standard PSO. Preliminary simulation results are presented considering simple continuous functions optimization examples.
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