Narrow Results

P. Jarratt has developed a family of fourth-order optimal methods. He suggested two members of the family. The dynamics of one of those was discussed previously. Here we show that the family can be written using a weight function and analyze all members of the family to find the best performer.

From some modifications of Chebyshev's method, we consider a uniparametric family of iterative methods that are more efficient than Newton's method, and we then construct two iterative methods in a similar way to the Secant method from Newton's method. These iterative methods do not use derivatives in their algorithms and one of them is more efficient than the Secant method, which is the classical method with this feature.

We present an extension of a well-known result of Traub to increase the R-order of convergence of one-point iterative methods by a simple modification of this type of methods. We consider the extension to one-point iterative methods with memory and present a particular case where Kurchatov's method is used. Moreover, we analyze the efficiency and the semilocal convergence of this method. Finally, two applications are presented, where differentiable and nondifferentiable equations are considered, that illustrate the above-mentioned.

We present derivative free multipoint methods of optimal eighth and sixteenth order convergence for solving nonlinear equations. The schemes are based on derivative free two-point methods proposed by Petković et al. [Petković, M. S., Džunić, J. and Petković, L. D. [2011] "A family of two-point methods with memory for solving nonlinear equations," Appl. Anal. Discrete Math.5, 298–317], which further developed by using rational approximations. Extending the work further, we explore four-point methods with memory with increasing order of convergence from the basic four-point scheme without memory. The order is increased from 16 of the basic method to 20, 22, 23, 23.662, and 24 by suitable variation of a free parameter in each iterative step. This increase in the convergence order is achieved without any additional function evaluations and therefore, the methods with memory possess better computational efficiency than the methods without memory. Numerical examples are presented and the performance is compared with the existing optimal three and four-point methods. Computational results and comparison with the existing methods confirm efficient and robust character of present methods.

In this paper, we discuss the convergence analysis of discontinuous finite volume methods applied to distribute the optimal control problems governed by a class of second-order linear elliptic equations. In order to approximate the control, two different methodologies are adopted: one is the method of variational discretization and second is piecewise constant discretization technique. For variational discretization method, optimal order of convergence in the $L^2$-norm for state, adjoint state and control variables is derived. Moreover, optimal order of convergence in discrete $H^1$-norm is also derived for state and adjoint state variables. Whereas, for piecewise constant approximation of control, first order convergence is derived for control, state and adjoint state variables in the $L^2$-norm. In addition to that, optimal order of convergence in discrete $H^1$-norm is derived for state and adjoint state variables. Also, some numerical experiments are conducted to support the derived theoretical convergence rate.

In this paper, we proposed a new highly efficient two-point sixth-order family of Halley type methods that do not require any second-order derivative evaluation for obtaining simple roots of nonlinear equations, numerically. In terms of computational cost, each member of the family requires two-function and two first-order derivative evaluations per iteration. On the account of the results obtained, it is found that our proposed methods are efficient and show better performance than existing sixth-order methods available in the literature. Further, it is also noted that larger basins of attraction belong to our methods as compared to the existing ones. On the other hand, the existing methods are slower and have darker basins while some of them are too sensitive upon the choice of the initial value.

In this study, we design a new efficient family of sixth-order iterative methods for solving scalar as well as system of nonlinear equations. The main beauty of the proposed family is that we have to calculate only one inverse of the Jacobian matrix in the case of nonlinear system which reduces the computational cost. The convergence properties are fully investigated along with two main theorems describing their order of convergence. By using complex dynamics tools, its stability is analyzed, showing stable members of the family. From this study, we intend to have more information about these methods in order to detect those with best stability properties. In addition, we also presented a numerical work which confirms the order of convergence of the proposed family is well deduced for scalar, as well as system of nonlinear equations. Further, we have also shown the implementation of the proposed techniques on real world problems like Van der Pol equation, Hammerstein integral equation, etc.

We develop some new iterative methods, using decomposition technique, for solving the problems which involve nonlinear equations. Importantly, these methods include the generalization of some well-known existing methods. We prove the convergence criteria of our newly proposed methods. Various test examples are considered to validate the efficiency of our new methods. We also give the numerical as well as graphical analysis for two mathematical models to endorse the performance of these methods.

In this work, a modified Newton–Özban composition of convergence order six for solving nonlinear systems is presented. The first two steps of proposed scheme are based on third-order method given by Özban [Özban, A. Y. [2004] “Some new variants of Newton’s method,” Appl. Math. Lett. 17, 677–682.] for solving scalar equations. Computational efficiency of the presented method is discussed and compared with well-known existing methods. Numerical examples are studied to demonstrate the accuracy of the proposed method. The basins of attraction of some of the existing methods along with the proposed method are given to exhibit their performance.

In this paper, a novel approximation to the Caputo time fractional derivative of variable order (VO) $\nu (\xi ,\eta )$ ($0<\nu (\xi ,\eta )<1$) is established. Since time fractional derivatives are integral, with a weakly singular kernel the discretization on the uniform mesh may not lead to satisfactory accuracy. So, numerical approximation is constructed on nonuniform meshes based on Newton interpolation polynomial. As a result, the novel approximation can be viewed as the modification of the existing method [Shen, S., Liu, F., Chen, J., Turner, I. and Anh, V. [2012] “Numerical techniques for the variable order time fractional diffusion equation,” Appl. Math. Comput. 218(22), 10861–10870]. The truncation errors and some significant properties of coefficients are analyzed. Furthermore, we derived Scheme-I and Scheme-II with second-order accuracy in spatial direction to solve the mobile–immobile advection–dispersion model (MIMADM) based on the VO Caputo derivative. The designed scheme converts the considered problems into a linear system of equations. Moreover, the stability properties of Scheme-I are discussed in detail. Ultimately, the proposed scheme is examined on several text examples demonstrating the high precision and effectiveness of the scheme. Also, comparative study between the outcomes achieved by implementing the suggested scheme with other numerical scheme in the existing literature is provided and also the acquired numerical results of these applications indicate that the suggested technique performs extremely well in terms of reliability and capability.

In this paper we introduce a family of one-point methods for multiple roots using weight functions. We analyze the necessary conditions for the weight function to achieve third-order accuracy, and then present a sequence of rational weight functions for a complex quadratic function. The resulting members of the family exhibit Julia sets that align with the perpendicular bisector of the roots. We compare selected members with existing methods based on basin of attraction analysis, demonstrating their competitive performance. Additionally, we investigate the influence of root multiplicity on the fractal structures of basin of attraction for equations with both simple and multiple roots.

There has been very less work done on developing methods for solving systems of nonlinear equations using the idea of memorization. Methods without memory can be extended to methods with memory without using any additional function evaluations. Improvement in the convergence order of methods with memory gives an added benefit. The stability of such methods is another important concept which needs to be considered. In this work, we deal with the development of such methods. We first construct a sixth-order derivative free family without memory and then further extend it to methods with memory of order $7.40,7.87$ and $8.77$. Numerical results show the superiority of these methods over the existing ones. Basins of attraction have also been presented to observe the dynamical behavior of the proposed methods and the comparison validates that the proposed methods are much more stable than the existing methods.

In this paper, we present some efficient iterative methods for solving nonlinear equation (systems of nonlinear equations, respectively) by using modified homotopy perturbation methods. We also discuss the convergence criteria of the present methods. Some numerical examples are given to illustrate the performance and efficiency of the proposed methods.

In this paper, we present new cubically convergent Newton-type iterative methods with dynamics for solving nonlinear algebraic equations under weak conditions. The proposed methods are free from second-order derivative and work well when $f^{\prime }(x)=0$. Numerical results show that the proposed method performs better when Newton’s method fails or diverges and competes well with same order existing method. Fractal patterns of different methods also support the numerical results and explain the compactness regarding the convergence, divergence, and stability of the methods to different roots.

We develop a new sixth-order accurate numerical scheme for the solution of two point boundary value problems. The scheme uses nonpolynomial spline basis and high order finite difference approximations. With the help of spline functions, we derive consistency conditions and it is used to derive high order discretizations of the first derivative. The resulting difference schemes are solved by the standard Newton's method and have very small computing time. The new method is analyzed for its convergence and the efficiency of the proposed scheme is illustrated by convection-diffusion problem and nonlinear Lotka–Volterra equation. The order of convergence and maximum absolute errors are computed to present the utility of the new scheme.

With the rapid development of information science and engineering technology, nonlinear problems become an important research in the field of numerical analysis. In this paper, iterative methods for solving nonlinear equations are researched. Two modified Newton-type algorithms for solving nonlinear equations are proposed and analyzed, whose order of convergence are six and seven respectively. Both of the methods are free from second derivatives. The efficiency index of the presented methods are 1.431 and 1.476, respectively, which are all better than that of the classical Newton’s method 1.414. Some numerical experiments demonstrate the performance of the presented algorithms.