Special Relativity Search: A novel metaheuristic method based on special relativity physics

Goodarzimehr, V; Shojaee, S; Hamzehei-Javaran, S; Talatahari, S

Special Relativity Search: A novel metaheuristic method based on special relativity physics

Goodarzimehr, V Shojaee, S Hamzehei-Javaran, S Talatahari, S

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Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Knowledge-Based Systems, 2022, 257, pp. 109484
Issue Date:: 2022-12

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Field	Value	Language
dc.contributor.author	Goodarzimehr, V
dc.contributor.author	Shojaee, S
dc.contributor.author	Hamzehei-Javaran, S
dc.contributor.author	Talatahari, S
dc.date.accessioned	2023-07-09T22:45:05Z
dc.date.available	2023-07-09T22:45:05Z
dc.date.issued	2022-12
dc.identifier.citation	Knowledge-Based Systems, 2022, 257, pp. 109484
dc.identifier.issn	0950-7051
dc.identifier.uri	http://hdl.handle.net/10453/171385
dc.description.abstract	In this work, a novel metaheuristic optimization algorithm called Special Relativity Search (SRS) is proposed. The SRS is inspired by the interaction of particles in an electromagnetic field. Particle interactions are calculated using the Lorentz force, and the equation of motion is developed using angular frequency. The magnetic force between particles is perpendicular to the velocity of charged particles and the magnetic field, which causes particles to move in a circular trajectory. In this method, for the first time, the theory of special relativity physics is utilized to determine the coordinates of charged particles in each rotation. The SRS main step equation is developed using the two phenomena of length contraction and time dilation. Charged particles are members of the initial population that is randomly generated, and their charge is determined based on their fitness. To show the efficiency and robustness of the SRS in solving optimization problems, 83 benchmark functions, which are a wide range of mathematical problems, are selected and optimized based on the values of Best, Mean, Median, and Standard Deviation (SD). The statistical test of the Wilcoxon Signed Ranks (WSR) is performed to fairly compare the results of this new method with other popular metaheuristic algorithms. The test results show that in most cases SRS is superior to other methods from the state-of-the-art. The results of evaluated optimization problems show that SRS is more effective and efficient compared to some other well-known metaheuristic methods in solving optimization problems.
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Knowledge-Based Systems
dc.relation.isbasedon	10.1016/j.knosys.2022.109484
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4605 Data management and data science
dc.subject.classification	4611 Machine learning
dc.title	Special Relativity Search: A novel metaheuristic method based on special relativity physics
dc.type	Journal Article
utslib.citation.volume	257
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
utslib.for	17 Psychology and Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-07-09T22:45:01Z
pubs.publication-status	Published
pubs.volume	257

Abstract:

In this work, a novel metaheuristic optimization algorithm called Special Relativity Search (SRS) is proposed. The SRS is inspired by the interaction of particles in an electromagnetic field. Particle interactions are calculated using the Lorentz force, and the equation of motion is developed using angular frequency. The magnetic force between particles is perpendicular to the velocity of charged particles and the magnetic field, which causes particles to move in a circular trajectory. In this method, for the first time, the theory of special relativity physics is utilized to determine the coordinates of charged particles in each rotation. The SRS main step equation is developed using the two phenomena of length contraction and time dilation. Charged particles are members of the initial population that is randomly generated, and their charge is determined based on their fitness. To show the efficiency and robustness of the SRS in solving optimization problems, 83 benchmark functions, which are a wide range of mathematical problems, are selected and optimized based on the values of Best, Mean, Median, and Standard Deviation (SD). The statistical test of the Wilcoxon Signed Ranks (WSR) is performed to fairly compare the results of this new method with other popular metaheuristic algorithms. The test results show that in most cases SRS is superior to other methods from the state-of-the-art. The results of evaluated optimization problems show that SRS is more effective and efficient compared to some other well-known metaheuristic methods in solving optimization problems.

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http://hdl.handle.net/10453/171385