Developing Chimp Optimization Algorithm for Function Estimation Tasks

This paper presents a novel approach for tackling the Lane-Emden equation, a significant nonlinear differential equation of paramount importance in the realms of physics and astrophysics. We employ the Chimp optimization algorithm in conjunction with Chebyshev polynomials to devise an innovative solution strategy. Inspired by the behavioral patterns of chimpanzees, the Chimp algorithm is harnessed to optimize the Chebyshev polynomial approximations, thereby transforming the Lane-Emden equation into an unconstrained optimization problem. Our method's effectiveness is demonstrated through a series of numerical experiments, showcasing its capability to precisely solve the Lane-Emden equation across various polytropic indices.