Exploring the Convergence Properties of a New Modified Newton-Raphson Root Method

We examine the convergence properties of a modified Newton-Raphson root method, by using a simple complex polynomial equation, as a test example. In particular, we numerically investigate how a parameter, entering the iterative scheme, affects the efficiency and the speed of the method. Color-coded polynomiographs are deployed for presenting the regions of convergence, as well as the fractality degree of the complex plane. We demonstrate that the behavior of the modified Newton-Raphson method is correlated with the numerical value of the parameter 1. Additionally, there are cases for which the method works flawlessly, while in some other cases we encounter the phenomena of ill-convergence or even non-convergence

Local convergence balls for nonlinear problems with multiplicity and their extension to eight-order of convergence

[EN] The main contribution of this study is to present a new optimal eighth-order scheme for locating zeros with multiplicity m > 1. An extensive convergence analysis is presented with the main theorem in order to demonstrate the optimal eighth-order convergence of the proposed scheme. Moreover, a local convergence study for the optimal fourth-order method defined by the first two steps of the new method is presented, allowing us to obtain the radius of the local convergence ball. Finally, numerical tests on some real-life problems, such as a Van der Waals equation of state, a conversion Chemical engineering problem and two standard academic test problems are presented, which confirm the theoretical results established in this paper and the efficiency of this proposed iterative method. We observed from the numerical experiments that our proposed iterative methods have good values for convergence radii. Further, they have not only faster convergence towards the desired zero of the involved function but they also have both smaller residual error and a smaller difference between two consecutive iterations than current existing techniques.This research was partially supported by Ministerio de Economia y Competitividad under grant MTM2014-52016-C2-2-P and by the project of Generalitat Valenciana Prometeo/2016/089.Behl, R.; Martínez Molada, E.; Cevallos-Alarcon, FA.; Alshomrani, AS. (2019). Local convergence balls for nonlinear problems with multiplicity and their extension to eight-order of convergence. Mathematical Problems in Engineering. 2019:1-18. https://doi.org/10.1155/2019/1427809S1182019Petković, M. S., Neta, B., Petković, L. D., & Džunić, J. (2013). Basic concepts. Multipoint Methods, 1-26. doi:10.1016/b978-0-12-397013-8.00001-7Shengguo, L., Xiangke, L., & Lizhi, C. (2009). A new fourth-order iterative method for finding multiple roots of nonlinear equations. Applied Mathematics and Computation, 215(3), 1288-1292. doi:10.1016/j.amc.2009.06.065Neta, B. (2010). Extension of Murakami’s high-order non-linear solver to multiple roots. International Journal of Computer Mathematics, 87(5), 1023-1031. doi:10.1080/00207160802272263Li, S. G., Cheng, L. Z., & Neta, B. (2010). Some fourth-order nonlinear solvers with closed formulae for multiple roots. Computers & Mathematics with Applications, 59(1), 126-135. doi:10.1016/j.camwa.2009.08.066Zhou, X., Chen, X., & Song, Y. (2011). Constructing higher-order methods for obtaining the multiple roots of nonlinear equations. Journal of Computational and Applied Mathematics, 235(14), 4199-4206. doi:10.1016/j.cam.2011.03.014Sharifi, M., Babajee, D. K. R., & Soleymani, F. (2012). Finding the solution of nonlinear equations by a class of optimal methods. Computers & Mathematics with Applications, 63(4), 764-774. doi:10.1016/j.camwa.2011.11.040Soleymani, F., & Babajee, D. K. R. (2013). Computing multiple zeros using a class of quartically convergent methods. Alexandria Engineering Journal, 52(3), 531-541. doi:10.1016/j.aej.2013.05.001Soleymani, F., Babajee, D. K. R., & Lotfi, T. (2013). On a numerical technique for finding multiple zeros and its dynamic. Journal of the Egyptian Mathematical Society, 21(3), 346-353. doi:10.1016/j.joems.2013.03.011Zhou, X., Chen, X., & Song, Y. (2013). Families of third and fourth order methods for multiple roots of nonlinear equations. Applied Mathematics and Computation, 219(11), 6030-6038. doi:10.1016/j.amc.2012.12.041Hueso, J. L., Martínez, E., & Teruel, C. (2014). Determination of multiple roots of nonlinear equations and applications. Journal of Mathematical Chemistry, 53(3), 880-892. doi:10.1007/s10910-014-0460-8Behl, R., Cordero, A., Motsa, S. S., & Torregrosa, J. R. (2015). On developing fourth-order optimal families of methods for multiple roots and their dynamics. Applied Mathematics and Computation, 265, 520-532. doi:10.1016/j.amc.2015.05.004Zafar, F., Cordero, A., Quratulain, R., & Torregrosa, J. R. (2017). Optimal iterative methods for finding multiple roots of nonlinear equations using free parameters. Journal of Mathematical Chemistry, 56(7), 1884-1901. doi:10.1007/s10910-017-0813-1Geum, Y. H., Kim, Y. I., & Neta, B. (2018). Constructing a family of optimal eighth-order modified Newton-type multiple-zero finders along with the dynamics behind their purely imaginary extraneous fixed points. Journal of Computational and Applied Mathematics, 333, 131-156. doi:10.1016/j.cam.2017.10.033Geum, Y. H., Kim, Y. I., & Magreñán, Á. A. (2018). A study of dynamics via Möbius conjugacy map on a family of sixth-order modified Newton-like multiple-zero finders with bivariate polynomial weight functions. Journal of Computational and Applied Mathematics, 344, 608-623. doi:10.1016/j.cam.2018.06.006Chun, C., & Neta, B. (2015). An analysis of a family of Maheshwari-based optimal eighth order methods. Applied Mathematics and Computation, 253, 294-307. doi:10.1016/j.amc.2014.12.064Thukral, R. (2013). Introduction to Higher-Order Iterative Methods for Finding Multiple Roots of Nonlinear Equations. Journal of Mathematics, 2013, 1-3. doi:10.1155/2013/404635Geum, Y. H., Kim, Y. I., & Neta, B. (2016). A sixth-order family of three-point modified Newton-like multiple-root finders and the dynamics behind their extraneous fixed points. Applied Mathematics and Computation, 283, 120-140. doi:10.1016/j.amc.2016.02.029Argyros, I. (2003). On The Convergence And Application Of Newton’s Method Under Weak HÖlder Continuity Assumptions. International Journal of Computer Mathematics, 80(6), 767-780. doi:10.1080/0020716021000059160Zhou, X., Chen, X., & Song, Y. (2013). On the convergence radius of the modified Newton method for multiple roots under the center–Hölder condition. Numerical Algorithms, 65(2), 221-232. doi:10.1007/s11075-013-9702-2Bi, W., Ren, H., & Wu, Q. (2011). Convergence of the modified Halley’s method for multiple zeros under Hölder continuous derivative. Numerical Algorithms, 58(4), 497-512. doi:10.1007/s11075-011-9466-5Zhou, X., & Song, Y. (2014). Convergence radius of Osada’s method under center-Hölder continuous condition. Applied Mathematics and Computation, 243, 809-816. doi:10.1016/j.amc.2014.06.068Cordero, 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.2007.01.062Balaji, 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. (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-

Widening basins of attraction of optimal iterative methods

[EN] In this work, we analyze the dynamical behavior on quadratic polynomials of a class of derivative-free optimal parametric iterative methods, designed by Khattri and Steihaug. By using their parameter as an accelerator, we develop different methods with memory of orders three, six and twelve, without adding new functional evaluations. Then a dynamical approach is made, comparing each of the proposed methods with the original ones without memory, with the following empiric conclusion: Basins of attraction of iterative schemes with memory are wider and the behavior is more stable. This has been numerically checked by estimating the solution of a practical problem, as the friction factor of a pipe and also of other nonlinear academic problems.This research was supported by Islamic Azad University, Hamedan Branch, Ministerio de Economia y Competitividad MTM2014-52016-C02-2-P and Generalitat Valenciana PROMETEO/2016/089.Bakhtiari, P.; Cordero Barbero, A.; Lotfi, T.; Mahdiani, K.; Torregrosa Sánchez, JR. (2017). Widening basins of attraction of optimal iterative methods. Nonlinear Dynamics. 87(2):913-938. https://doi.org/10.1007/s11071-016-3089-2S913938872Amat, S., Busquier, S., Bermúdez, C., Plaza, S.: On two families of high order Newton type methods. Appl. Math. Lett. 25, 2209–2217 (2012)Amat, S., Busquier, S., Bermúdez, C., Magreñán, Á.A.: On the election of the damped parameter of a two-step relaxed Newton-type method. Nonlinear Dyn. 84(1), 9–18 (2016)Chun, C., Neta, B.: An analysis of a family of Maheshwari-based optimal eighth order methods. Appl. Math. Comput. 253, 294–307 (2015)Babajee, D.K.R., Cordero, A., Soleymani, F., Torregrosa, J.R.: On improved three-step schemes with high efficiency index and their dynamics. Numer. Algorithms 65(1), 153–169 (2014)Argyros, I.K., Magreñán, Á.A.: On the convergence of an optimal fourth-order family of methods and its dynamics. Appl. Math. Comput. 252, 336–346 (2015)Petković, M., Neta, B., Petković, L., Džunić, J.: Multipoint Methods for Solving Nonlinear Equations. Academic Press, London (2013)Ostrowski, A.M.: Solution of Equations and System of Equations. Prentice-Hall, Englewood Cliffs, NJ (1964)Kung, H.T., Traub, J.F.: Optimal order of one-point and multipoint iteration. J. ACM 21, 643–651 (1974)Khattri, S.K., Steihaug, T.: Algorithm for forming derivative-free optimal methods. Numer. Algorithms 65(4), 809–824 (2014)Traub, J.F.: Iterative Methods for the Solution of Equations. Prentice Hall, New York (1964)Cordero, A., Soleymani, F., Torregrosa, J.R., Shateyi, S.: Basins of Attraction for Various Steffensen-Type Methods. J. Appl. Math. 2014, 1–17 (2014)Devaney, R.L.: The Mandelbrot Set, the Farey Tree and the Fibonacci sequence. Am. Math. Mon. 106(4), 289–302 (1999)McMullen, C.: Families of rational maps and iterative root-finding algorithms. Ann. Math. 125(3), 467–493 (1987)Chicharro, F., Cordero, A., Gutiérrez, J.M., Torregrosa, J.R.: Complex dynamics of derivative-free methods for nonlinear equations. Appl. Math. Comput. 219, 70237035 (2013)Magreñán, Á.A.: Different anomalies in a Jarratt family of iterative root-finding methods. Appl. Math. Comput. 233, 29–38 (2014)Neta, B., Chun, C., Scott, M.: Basins of attraction for optimal eighth order methods to find simple roots of nonlinear equations. Appl. Math. 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An analysis of a family of Maheshwari-based optimal eighth order methods

The article of record as published may be found at http://dx.doi.org/10.1016/j.amc.2014.12.064In this paper we analyze an optimal eighth-order family of methods based on Maheshwari’s fourth order method. This family of methods uses a weight function. We analyze the family using the information on the extraneous fixed points. Two measures of closeness of an extraneous points set to the imaginary axis are considered and applied to the members of the family to find its best performer. The results are compared to a modified version of Wang–Liu method.Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2005012)Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2005012

Métodos iterativos para la resolución de problemas aplicados transformados a sistemas no lineales

[ES] La resolución de ecuaciones y sistemas no lineales es un tema de gran interés teórico-práctico, pues muchos modelos matemáticos de la ciencia o de la industria se expresan mediante sistemas no lineales o ecuaciones diferenciales o integrales que, mediante técnicas de discretización, dan lugar a dichos sistemas. Dado que generalmente es difícil, si no imposible, resolver analíticamente las ecuaciones no lineales, la herramienta más extendida son los métodos iterativos, que tratan de obtener aproximaciones cada vez más precisas de las soluciones partiendo de determinadas estimaciones iniciales. Existe una variada literatura sobre los métodos iterativos para resolver ecuaciones y sistemas, que abarca conceptos como, eficiencia, optimalidad, estabilidad, entre otros importantes temas. En este estudio obtenemos nuevos métodos iterativos que mejoran algunos conocidos en términos de orden o eficiencia, es decir que obtienen mejores aproximaciones con menor coste computacional. La convergencia de los métodos iterativos suele estudiarse desde el punto de vista local. Esto significa que se obtienen resultados de convergencia imponiendo condiciones a la ecuación en un entorno de la solución. Obviamente, estos resultados no son aplicables si no la conocemos. Otro punto de vista, que abordamos en este trabajo, es el estudio semilocal que, imponiendo condiciones en un entorno de la estimación inicial, proporciona un entorno de dicho punto que contiene la solución y garantiza la convergencia del método iterativo a la misma. Finalmente, desde un punto de vista global, estudiamos el comportamiento de los métodos iterativos en función de la estimación inicial, mediante el estudio de la dinámica de las funciones racionales asociadas a estos métodos. La presente memoria recoge los resultados de varios artículos de nuestra autoría, en los que se tratan distintos aspectos de la materia, como son, las peculiaridades de la convergencia en el caso de raíces múltiples, la posibilidad de aumentar el orden de un método óptimo de orden cuatro a orden ocho, manteniendo la optimalidad en el caso de raíces múltiples, el estudio de la convergencia semilocal en un método de alto orden, así como el comportamiento dinámico de algunos métodos iterativos.[CA] La resolució d'equacions i sistemes no lineals és un tema de gran interés teoricopràctic, perquè molts models matemàtics de la ciència o de la indústria s'expressen mitjançant sistemes no lineals o equacions diferencials o integrals que, mitjançant tècniques de discretizació, donen lloc a aquests sistemes. Atés que generalment és difícil, si no impossible, resoldre analíticament les equacions no lineals, l'eina més estesa són els mètodes iteratius, que tracten d'obtindre aproximacions cada vegada més precises de les solucions partint de determinades estimacions inicials. Existeix una variada literatura sobre els mètodes iteratius per a resoldre equacions i sistemes, que abasta conceptes com ordre d'aproximació, eficiència, optimalitat, estabilitat, entre altres importants temes. En aquest estudi obtenim nous mètodes iteratius que milloren alguns coneguts en termes d'ordre o eficiència, és a dir que obtenen millors aproximacions amb menor cost computacional. La convergència dels mètodes iteratius sol estudiar-se des del punt de vista local. Això significa que s'obtenen resultats de convergència imposant condicions a l'equació en un entorn de la solució. Òbviament, aquests resultats no són aplicables si no la coneixem. Un altre punt de vista, que abordem en aquest treball, és l'estudi semilocal que, imposant condicions en un entorn de l'estimació inicial, proporciona un entorn d'aquest punt que conté la solució i garanteix la convergència del mètode iteratiu a aquesta. Finalment, des d'un punt de vista global, estudiem el comportament dels mètodes iteratius en funció de l'estimació inicial, mitjançant l'estudi de la dinàmica de les funcions racionals associades a aquests mètodes. La present memòria recull els resultats de diversos articles de la nostra autoria, en els quals es tracten diferents aspectes de la matèria, com són, les peculiaritats de la convergència en el cas d'arrels múltiples, la possibilitat d'augmentar l'ordre d'un mètode òptim d'ordre quatre a ordre huit, mantenint l'optimalitat en el cas d'arrels múltiples, l'estudi de la convergència semilocal en un mètode d'alt ordre, així com el comportament dinàmic d'alguns mètodes iteratius.[EN] The resolution of nonlinear equations and systems is a subject of great theoretical and practical interest, since many mathematical models in science or industry are expressed through nonlinear systems or differential or integral equations that, by means of discretization techniques, give rise to such systems. Since it is generally difficult, if not impossible, to solve nonlinear equations analytically, the most widely used tool is iterative methods, which try to obtain increasingly precise approximations of the solutions based on certain initial estimates. There is a varied literature on iterative methods for solving equations and systems, which covers concepts of order of approximation, efficiency, optimality, stability, among other important topics. In this study we obtain new iterative methods that improve some known ones in terms of order or efficiency, that is, they obtain better approximations with lower computational cost. The convergence of iterative methods is usually studied locally. This means that convergence results are obtained by imposing conditions on the equation in a neighbourhood of the solution. Obviously, these results are not applicable if we do not know it. Another point of view, which we address in this work, is the semilocal study that, by imposing conditions in a neighbourhood of the initial estimation, provides an environment of this point that contains the solution and guarantees the convergence of the iterative method to it. Finally, from a global point of view, we study the behaviour of iterative methods as a function of the initial estimation, by studying the dynamics of the rational functions associated with these methods. This report collects the results of several articles of our authorship, in which different aspects of the matter are dealt with, such as the peculiarities of convergence in the case of multiple roots, the possibility of increasing the order of an optimal method from order four to order eight, maintaining optimality in the case of multiple roots, the study of semilocal convergence in a high-order method, as well as the dynamic behaviour of some iterative methods.Cevallos Alarcón, FA. (2023). Métodos iterativos para la resolución de problemas aplicados transformados a sistemas no lineales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19349