A heuristic to determine the initial gravitational constant of the GSA

The Gravitational Search Algorithm (GSA) is an optimization algorithm based on Newton's laws of gravity and dynamics. Introduced in 2009, the GSA already has several versions and applications. However, its performance depends on the values of its parameters, which are determined empirically. He...

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Bibliographic Details
Main Authors:	Barbosa, Alfredo J. P, Moreira, Edmilson M, Moraes, Carlos H. V, Carpinteiro, Otávio A. S
Format:	Journal Article
Language:	English
Published:	21-04-2022
Subjects:	Computer Science - Artificial Intelligence Computer Science - Neural and Evolutionary Computing
Online Access:	Get full text
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Summary:	The Gravitational Search Algorithm (GSA) is an optimization algorithm based on Newton's laws of gravity and dynamics. Introduced in 2009, the GSA already has several versions and applications. However, its performance depends on the values of its parameters, which are determined empirically. Hence, its generality is compromised, because the parameters that are suitable for a particular application are not necessarily suitable for another. This paper proposes the Gravitational Search Algorithm with Normalized Gravitational Constant (GSA-NGC), which defines a new heuristic to determine the initial gravitational constant of the GSA. The new heuristic is grounded in the Brans-Dicke theory of gravitation and takes into consideration the multiple dimensions of the search space of the application. It aims to improve the final solution and reduce the number of iterations and premature convergences of the GSA. The GSA-NGC is validated experimentally, proving to be suitable for various applications and improving significantly the generality, performance, and efficiency of the GSA.
DOI:	10.48550/arxiv.2205.06770