A family of iterative methods with accelerated eighth-order convergence

We propose a family of eighth-order iterative methods without memory for solving nonlinear equations. The new iterative methods are developed by using weight function method and using an approximation for the last derivative, which reduces the required number of functional evaluations per step. Their efficiency indices are all found to be 1.682. Several examples allow us to compare our algorithms with known ones and confirm the theoretical results.The authors would like to thank the referee for the valuable comments and for the suggestions to improve the readability of the paper. This research was supported by Ministerio de Ciencia y Tecnologia MTM2011-28636-C02-02 and by Vicerrectorado de Investigacion, Universitat Politecnica de Valencia PAID-06-2010-2285.Cordero Barbero, A.; Fardi, M.; Ghasemi, M.; Torregrosa Sánchez, JR. (2012). A family of iterative methods with accelerated eighth-order convergence. Journal of Applied Mathematics. 2012. https://doi.org/10.1155/2012/2825612012Jarratt, P. (1966). Some fourth order multipoint iterative methods for solving equations. Mathematics of Computation, 20(95), 434-434. doi:10.1090/s0025-5718-66-99924-8Homeier, H. H. H. (2005). On Newton-type methods with cubic convergence. Journal of Computational and Applied Mathematics, 176(2), 425-432. doi:10.1016/j.cam.2004.07.027Kung, H. T., & Traub, J. F. (1974). Optimal Order of One-Point and Multipoint Iteration. Journal of the ACM, 21(4), 643-651. doi:10.1145/321850.321860King, R. F. (1973). A Family of Fourth Order Methods for Nonlinear Equations. SIAM Journal on Numerical Analysis, 10(5), 876-879. doi:10.1137/0710072Chun, C. (2007). Some variants of King’s fourth-order family of methods for nonlinear equations. Applied Mathematics and Computation, 190(1), 57-62. doi:10.1016/j.amc.2007.01.006Chun, C. (2008). Some fourth-order iterative methods for solving nonlinear equations. Applied Mathematics and Computation, 195(2), 454-459. doi:10.1016/j.amc.2007.04.105Chun, C., Lee, M. Y., Neta, B., & Džunić, J. (2012). On optimal fourth-order iterative methods free from second derivative and their dynamics. Applied Mathematics and Computation, 218(11), 6427-6438. doi:10.1016/j.amc.2011.12.013Maheshwari, A. K. (2009). A fourth order iterative method for solving nonlinear equations. Applied Mathematics and Computation, 211(2), 383-391. doi:10.1016/j.amc.2009.01.047Neta, B. (1981). On a family of multipoint methods for non-linear equations. International Journal of Computer Mathematics, 9(4), 353-361. doi:10.1080/00207168108803257Bi, W., Ren, H., & Wu, Q. (2009). Three-step iterative methods with eighth-order convergence for solving nonlinear equations. Journal of Computational and Applied Mathematics, 225(1), 105-112. doi:10.1016/j.cam.2008.07.004Cordero, A., Torregrosa, J. R., & Vassileva, M. P. (2011). Three-step iterative methods with optimal eighth-order convergence. Journal of Computational and Applied Mathematics, 235(10), 3189-3194. doi:10.1016/j.cam.2011.01.004Liu, L., & Wang, X. (2010). Eighth-order methods with high efficiency index for solving nonlinear equations. Applied Mathematics and Computation, 215(9), 3449-3454. doi:10.1016/j.amc.2009.10.040Cordero, A., & Torregrosa, J. R. (2007). Variants of Newton’s Method using fifth-order quadrature formulas. Applied Mathematics and Computation, 190(1), 686-698. doi:10.1016/j.amc.2007.01.06

Multidimensional Homeier's generalized class and its application to planar 1D Bratu problem

[EN] In this paper, a parametric family of iterative methods for solving nonlinear systems, including Homeier’s scheme is presented, proving its third-order of convergence. The numerical section is devoted to obtain an estimation of the solution of the classical Bratu problem by transforming it in a nonlinear system by using finite differences, and solving it with different elements of the iterative family.This research was supported by Ministerio de Economía y Competitividad MTM2014-52016-C02-02.Cordero Barbero, A.; Franqués García, AM.; Torregrosa Sánchez, JR. (2015). Multidimensional Homeier's generalized class and its application to planar 1D Bratu problem. Journal of the Spanish Society of Applied Mathematics. 70(1):1-10. https://doi.org/10.1007/s40324-015-0037-xS110701Abad, M. F., Cordero, A., Torregrosa, J. R.: Fourth-and fifth-order for solving nonlinear systems of equations: an application to the global positioning system, Abstr. Appl. Anal. (2013) (Article ID 586708)Andreu, C., Cambil, N., Cordero, A., Torregrosa, J.R.: Preliminary orbit determination of artificial satellites: a vectorial sixth-order approach, Abstr. Appl. Anal. (2013) (Article ID 960582)Awawdeh, F.: On new iterative method for solving systems of nonlinear equations. Numer. Algorithms 54, 395–409 (2010)Boyd, J.P.: One-point pseudospectral collocation for the one-dimensional Bratu equation. Appl. Math. Comput. 217, 5553–5565 (2011)Bratu, G.: Sur les equation integrals non-lineaires. Bull. Math. Soc. France 42, 113–142 (1914)Buckmire, R.: Applications of Mickens finite differences to several related boundary value problems. In: Mickens, R.E. (ed.) Advances in the Applications of Nonstandard Finite Difference Schemes, pp. 47–87. World Scientific Publishing, Singapore (2005)Cordero, A., Hueso, J.L., Martínez, E., Torregrosa, J.R.: A modified Newton-Jarratt’s composition. Numer. Algorithms 55, 87–99 (2010)Gelfand, I.M.: Some problems in the theory of quasi-linear equations. Trans. Am. Math. Soc. Ser. 2, 295–381 (1963)Homeier, H.H.H.: On Newton-tyoe methods with cubic convergence. J. Comput. Appl. Math. 176, 425–432 (2005)Jacobsen, J., Schmitt, K.: The Liouville-Bratu-Gelfand problem for radial operators. J. Differ. Equ. 184, 283–298 (2002)Jalilian, R.: Non-polynomial spline method for solving Bratu’s problem. Comput. Phys. Comm. 181, 1868–1872 (2010)Kanwar, V., Kumar, S., Behl, R.: Several new families of Jarratts method for solving systems of nonlinear equations. Appl. Appl. Math. 8(2), 701–716 (2013)Mohsen, A.: A simple solution of the Bratu problem. Comput. Math. with Appl. 67, 26–33 (2014)Petković, M., Neta, B., Petković, L., Džunić, J.: Multipoint Methods for Solving Nonlinear Equations. Academic Press, Amsterdam (2013)Sharma, J.R., Guna, R.K., Sharma, R.: An efficient fourth order weighted-Newton method for systems of nonlinear equations. Numer. Algorithms 62, 307–323 (2013)Sharma, J.R., Arora, H.: On efficient weighted-Newton methods for solving systems of nonlinear equations. Appl. Math. Comput. 222, 497–506 (2013)Traub, J.F.: Iterative Methods for the Solution of Equations. Chelsea Publishing Company, New York (1982)Wan, Y.Q., Guo, Q., Pan, N.: Thermo-electro-hydrodynamic model for electrospinning process. Int. J. Nonlinear Sci. Numer. Simul. 5, 5–8 (2004

Impact on stability by the use of memory in Traub-type schemes

[EN] In this work, two Traub-type methods with memory are introduced using accelerating parameters. To obtain schemes with memory, after the inclusion of these parameters in Traub's method, they have been designed using linear approximations or the Newton's interpolation polynomials. In both cases, the parameters use information from the current and the previous iterations, so they define a method with memory. Moreover, they achieve higher order of convergence than Traub's scheme without any additional functional evaluations. The real dynamical analysis verifies that the proposed methods with memory not only converge faster, but they are also more stable than the original scheme. The methods selected by means of this analysis can be applied for solving nonlinear problems with a wider set of initial estimations than their original partners. This fact also involves a lower number of iterations in the process.This research was partially supported by Ministerio de Ciencia, Innovacion y Universidades under grants PGC2018-095896-B-C22 (MCIU/AEI/FEDER/UE).Chicharro, FI.; Cordero Barbero, A.; Garrido, N.; Torregrosa Sánchez, JR. (2020). Impact on stability by the use of memory in Traub-type schemes. Mathematics. 8(2):1-16. https://doi.org/10.3390/math8020274S11682Shacham, M. (1989). An improved memory method for the solution of a nonlinear equation. Chemical Engineering Science, 44(7), 1495-1501. doi:10.1016/0009-2509(89)80026-0Balaji, G. V., & Seader, J. D. (1995). Application of interval Newton’s method to chemical engineering problems. Reliable Computing, 1(3), 215-223. doi:10.1007/bf02385253Shacham, M. (1986). Numerical solution of constrained non-linear algebraic equations. International Journal for Numerical Methods in Engineering, 23(8), 1455-1481. doi:10.1002/nme.1620230805Shacham, M., & Kehat, E. (1973). Converging interval methods for the iterative solution of a non-linear equation. Chemical Engineering Science, 28(12), 2187-2193. doi:10.1016/0009-2509(73)85008-0Amat, S., Busquier, S., & Plaza, S. (2010). Chaotic dynamics of a third-order Newton-type method. Journal of Mathematical Analysis and Applications, 366(1), 24-32. doi:10.1016/j.jmaa.2010.01.047Argyros, I. K., Cordero, A., Magreñán, Á. A., & Torregrosa, J. R. (2017). Third-degree anomalies of Traub’s method. Journal of Computational and Applied Mathematics, 309, 511-521. doi:10.1016/j.cam.2016.01.060Chicharro, F., Cordero, A., Gutiérrez, J. M., & Torregrosa, J. R. (2013). Complex dynamics of derivative-free methods for nonlinear equations. Applied Mathematics and Computation, 219(12), 7023-7035. doi:10.1016/j.amc.2012.12.075Chicharro, F., Cordero, A., & Torregrosa, J. (2015). Dynamics and Fractal Dimension of Steffensen-Type Methods. Algorithms, 8(2), 271-279. doi:10.3390/a8020271Scott, M., Neta, B., & Chun, C. (2011). Basin attractors for various methods. Applied Mathematics and Computation, 218(6), 2584-2599. doi:10.1016/j.amc.2011.07.076Steffensen, J. F. (1933). Remarks on iteration. Scandinavian Actuarial Journal, 1933(1), 64-72. doi:10.1080/03461238.1933.10419209Wang, X., & Zhang, T. (2012). A new family of Newton-type iterative methods with and without memory for solving nonlinear equations. Calcolo, 51(1), 1-15. doi:10.1007/s10092-012-0072-2Džunić, J., & Petković, M. S. (2014). On generalized biparametric multipoint root finding methods with memory. Journal of Computational and Applied Mathematics, 255, 362-375. doi:10.1016/j.cam.2013.05.013Petković, M. S., Neta, B., Petković, L. D., & Džunić, J. (2014). Multipoint methods for solving nonlinear equations: A survey. Applied Mathematics and Computation, 226, 635-660. doi:10.1016/j.amc.2013.10.072Campos, B., Cordero, A., Torregrosa, J. R., & Vindel, P. (2015). A multidimensional dynamical approach to iterative methods with memory. Applied Mathematics and Computation, 271, 701-715. doi:10.1016/j.amc.2015.09.056Chicharro, F. I., Cordero, A., & Torregrosa, J. R. (2019). Dynamics of iterative families with memory based on weight functions procedure. Journal of Computational and Applied Mathematics, 354, 286-298. doi:10.1016/j.cam.2018.01.019Chicharro, F. I., Cordero, A., Torregrosa, J. R., & Vassileva, M. P. (2017). King-Type Derivative-Free Iterative Families: Real and Memory Dynamics. Complexity, 2017, 1-15. doi:10.1155/2017/2713145Magreñán, Á. A., Cordero, A., Gutiérrez, J. M., & Torregrosa, J. R. (2014). Real qualitative behavior of a fourth-order family of iterative methods by using the convergence plane. Mathematics and Computers in Simulation, 105, 49-61. doi:10.1016/j.matcom.2014.04.006Blanchard, P. (1984). Complex analytic dynamics on the Riemann sphere. Bulletin of the American Mathematical Society, 11(1), 85-141. doi:10.1090/s0273-0979-1984-15240-6Magreñán, Á. A. (2014). A new tool to study real dynamics: The convergence plane. Applied Mathematics and Computation, 248, 215-224. doi:10.1016/j.amc.2014.09.061Chicharro, F. I., Cordero, A., & Torregrosa, J. R. (2013). Drawing Dynamical and Parameters Planes of Iterative Families and Methods. The Scientific World Journal, 2013, 1-11. doi:10.1155/2013/78015

Some Classes of third and Fourth-order iterative methods for solving nonlinear equations

The object of the present work is to present the new classes of third-order and fourth-order iterative methods for solving nonlinear equations. Our third-order method includes methods of Weerakoon \cite{Weerakoon}, Homeier \cite{Homeier2}, Chun \cite{Chun} e.t.c. as particular cases. After that we make this third-order method to fourth-order (optimal) by using a single weight function rather than using two different weight functions in \cite{Soleymani}. Finally some examples are given to illustrate the performance of the our method by comparing with new existing third and fourth-order methods.Comment: arXiv admin note: substantial text overlap with arXiv:1307.733