Modified spectral conjugate gradient iterative scheme for unconstrained optimization problems with application on COVID-19 model - Novkaniza, Fevi; Malik, Maulana; Sulaiman, Ibrahim Mohammed; Aldila, Dipo (Frontiers in Applied Mathematics and Statistics, 2022)
In this work, a new class of spectral conjugate gradient (CG) method is proposed for solving unconstrained optimization models. The search direction of the new method uses ZPRP and JYJLL CG coefficient. The search direction satisfies the descent condition independent of the line search. The global convergence properties of the proposed method under the strong Wolfe line search are proved with some certain assumptions. Based on some test functions, numerical experiments are presented to show the efficiency of the proposed method and compared it with other existing methods. The application of the proposed method for solving regression models of COVID-19 is provided.