A novel hybrid approach using the Jaya algorithm and rational Chebyshev polynomials for solving Lane-Emden type equations in astrophysical applications

Akbarzadeh, Arman; Dana Mazraeh, Hassan; Parand, Kourosh

doi:10.22060/ajmc.2025.24513.1432

A novel hybrid approach using the Jaya algorithm and rational Chebyshev polynomials for solving Lane-Emden type equations in astrophysical applications

Articles in Press

Document Type : Original Article

Authors

Arman Akbarzadeh ¹

Hassan Dana Mazraeh ²

Kourosh Parand ²^{, 3}

¹ Department of Computer and Data Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran

² School of Mathematics and Computer Sciences, Damghan University, P.O. Box 36715-364, Damghan, Iran

³ Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran

10.22060/ajmc.2025.24513.1432

Abstract

The Jaya algorithm is a population-based metaheuristic algorithm used for solving optimization problems. The algorithm's fundamental principle revolves around generating an initial random population. Through iterative refinement using update rules, the goal is to bring the solution closer to the optimal outcome while concurrently distancing it from suboptimal results. This paper presents the application of the Jaya algorithm in solving the Lane-Emden type equations using rational Chebyshev polynomials and standard polynomials as base functions. The results indicate that the Jaya algorithm is a reliable and capable method for solving the Lane-Emden type equations.

Keywords

Lane-Emden equations

Jaya algorithm

Rational Chebyshev polynomials

Metaheuristic algorithm

Subjects