A modification of gravitational search algorithm with hyper-ellipsoids
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Date
2019
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Publisher
Maltepe Üniversitesi
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CC0 1.0 Universal
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
Abstract
Gravitational Search Algorithm (GSA) is one of the popular nature inspired metaheuristic method, using the theory of Newtonian’s law of gravity and motion in physics. Till now, many variants of GSA have been presented in order to solve different kinds of optimization problems. In the current work, we develepod original GSA algorithm using dynamically generated swarm size with mutation operator. For this aim, we generate population inside of and outside of hyper-ellipsoids. Thus, the exploitation and exploration ability of GSA has been improved. We test the performance of proposed approach using some popular benchmark functions including both of low and high dimensional cases. We get the results of proposed approach and original GSA and compare them. According to results, we could say the proposed approach is better alternative for original GSA. Moreover, other population based methods can be improved with this way
Description
Keywords
Metaheuristic, Swarm intelligence, Gravitational search algorithm, Global optimization, Hhyperellipsoid
Journal or Series
International Conference of Mathematical Sciences (ICMS 2019)
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Citation
Gör, İ. ve Günel, K. (2019). A modification of gravitational search algorithm with hyper-ellipsoids. International Conference of Mathematical Sciences (ICMS 2019). s. 150.
