A heuristic to determine the initial gravitational constant of the GSA

TL;DR

This paper introduces a heuristic based on Brans-Dicke theory to set the initial gravitational constant in GSA, enhancing its adaptability, efficiency, and solution quality across diverse applications.

Contribution

It proposes GSA-NGC, a new heuristic for initial parameter setting in GSA, grounded in gravitational theory and considering search space dimensions, improving performance and generality.

Findings

GSA-NGC improves solution quality across applications

Reduces number of iterations and premature convergence

Enhances GSA's adaptability and efficiency

Abstract

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.