Multiple Roots Of Nonlinear Equations Research Articles

On a Sixth-order Solver for Multiple Roots of Nonlinear Equations

A number of iterative schemes with high convergence order to solve nonlinear equations are presented in the literature. In this paper, a sixth-order multiple-zero finder has been developed and the dynamics of selected iterative schemes with uniparametric polynomial weight function are investigated using M\"{o}bius conjugacy map applied to the form $((z-A)(z-B))^m$. The complex dynamics on the Riemann sphere by analyzing the parameter spaces associated with the free critical points are studied and the numerical experiments are carried out.

A robust iterative family for multiple roots of nonlinear equations: Enhancing accuracy and handling critical points

Numerous branches of applied science and engineering commonly encounter nonlinear equations that must be solved using effective numerical techniques. This research article introduces an iterative method that exhibits an optimal fourth-order convergence rate, ensuring rapid and accurate approximation of the roots. Unlike conventional methods, the proposed algorithm can successfully converge even when the derivative is zero or approaches zero in the vicinity of the desired root. This remarkable feature enhances the applicability of the method, allowing it to handle situations where conventional methods fail due to the presence of critical points such as the roots of f′(x)=0. The convergence analysis of the proposed method is presented, showing its superior performance compared to other methods. Extensive numerical experiments are conducted to validate the efficiency and accuracy of the algorithm. The results indicate that the proposed iterative method not only achieves fast convergence but also exhibits robustness in handling various types of nonlinear equations. Its ability to converge even in the presence of zero or near-zero derivatives significantly expands the scope of applications, making it a valuable tool for solving complex problems in science and engineering.

Modifying Kurchatov's method to find multiple roots of nonlinear equations

We present a modification of Kurchatov's iterative method in order to solve a nonlinear equation with multiple roots, that is, for approximating solutions with multiplicity greater than one. One of its principal advantages is that you do not have to know a priori the multiplicity of the root, since it does not appear in the iterative expression. In order to examine the behaviour of the proposed method, we perform a dynamical analysis. Furthermore, we carry out some numerical experiments in order to confirm the theoretical results and compare the proposed method with other known methods for dealing with multiple roots.

On a Fifth-Order Method for Multiple Roots of Nonlinear Equations

There are several measures for comparing methods for solving a single nonlinear equation. The first is the order of convergence, then the cost to achieve such rate. This cost is measured by counting the number of functions (and derivatives) evaluated at each step. After that, efficiency is defined as a function of the order of convergence and cost. Lately, the idea of basin of attraction is used. This shows how far one can start and still converge to the root. It also shows the symmetry/asymmetry of the method. It was shown that even methods that show symmetry when solving polynomial equations are not so when solving nonpolynomial ones. We will see here that the Euler–Cauchy method (a member of the Laguerre family of methods for multiple roots) is best in the sense that the boundaries of the basins have no lobes. The symmetry in solving a polynomial equation having two roots at ±1 with any multiplicity is obvious. In fact, the Euler–Cauchy method converges very fast in this case. We compare one member of a family of fifth-order methods for multiple roots with several well-known lower-order and efficient methods. We will show using a basin of attraction that the fifth-order method cannot compete with most of those lower-order methods.

Novel Parametric Families of with and without Memory Iterative Methods for Multiple Roots of Nonlinear Equations

The methods that use memory using accelerating parameters for computing multiple roots are almost non-existent in the literature. Furthermore, the only paper available in this direction showed an increase in the order of convergence of 0.5 from the without memory to the with memory extension. In this paper, we introduce a new fifth-order without memory method, which we subsequently extend to two higher-order with memory methods using a self-accelerating parameter. The proposed with memory methods extension demonstrate a significant improvement in the order of convergence from 5 to 7, making this the first paper to achieve at least a 2-order improvement. In addition to this improvement, our paper is also the first to use Hermite interpolating polynomials to approximate the accelerating parameter in the proposed with memory methods for multiple roots. We also provide rigorous theoretical proofs of convergence theorems to establish the order of the proposed methods. Finally, we demonstrate the potential impact of the proposed methods through numerical experimentation on a diverse range of problems. Overall, we believe that our proposed methods have significant potential for various applications in science and engineering.

A New Third-Order Family of Multiple Root-Findings Based on Exponential Fitted Curve

In this paper, we present a new third-order family of iterative methods in order to compute the multiple roots of nonlinear equations when the multiplicity (m≥1) is known in advance. There is a plethora of third-order point-to-point methods, available in the literature; but our methods are based on geometric derivation and converge to the required zero even though derivative becomes zero or close to zero in vicinity of the required zero. We use the exponential fitted curve and tangency conditions for the development of our schemes. Well-known Chebyshev, Halley, super-Halley and Chebyshev–Halley are the special members of our schemes for m=1. Complex dynamics techniques allows us to see the relation between the element of the family of iterative schemes and the wideness of the basins of attraction of the simple and multiple roots, on quadratic polynomials. Several applied problems are considered in order to demonstrate the performance of our methods and for comparison with the existing ones. Based on the numerical outcomes, we deduce that our methods illustrate better performance over the earlier methods even though in the case of multiple roots of high multiplicity.

On numerical schemes for determination of all roots simultaneously of non-linear equation

In this article, we first construct family of two-step optimal fourth order iterative methods for finding single root of non-linear equation. We then extend these methods for determining all the distinct as well as multiple roots of single variable non-linear equation simultaneously. Convergence analysis is presented for both the cases to show that the optimal order of convergence is 4 in case of single root finding method and 6 for simultaneous determination of all distinct as well as multiple roots of a non-linear equation. The computational cost, basins of attraction, computational efficiency, log of residual fall and numerical test functions validate that the newly constructed methods are more efficient as compared to the existing methods in the literature.

A new higher-order optimal derivative free scheme for multiple roots

In this paper, we presented a novel and efficient fourth order derivative free optimal family of iterative methods for approximating the multiple roots of nonlinear equations. Initially the convergence analysis is performed for particular values of multiple roots afterward it concludes in general form. In addition, we study several numerical experiments on real life problems in order to confirm the efficiency and accuracy of our methods. We illustrate the applicability and comparisons of our methods on eigenvalue problem, Van der Waals equation of state, continuous stirred tank reactor (CSTR), Plank’s radiation and clustering problem of roots with earlier robust iterative methods. Finally, on the basis of obtained computational results, we conclude that our methods perform better than the existing ones in terms of CPU timing, absolute residual errors, asymptotic error constants, absolute error difference between two last consecutive iterations and approximated roots compared to the existing ones.

A Family of Fifth-Order Iterative Methods for Finding Multiple Roots of Nonlinear Equations

A Family of Fifth-Order Iterative Methods for Finding Multiple Roots of Nonlinear Equations

A Family of Optimal Eighth Order Iteration Functions for Multiple Roots and Its Dynamics

In this manuscript, we present a new general family of optimal iterative methods for finding multiple roots of nonlinear equations with known multiplicity using weight functions. An extensive convergence analysis is presented to verify the optimal eighth order convergence of the new family. Some special cases of the family are also presented which require only three functions and one derivative evaluation at each iteration to reach optimal eighth order convergence. A variety of numerical test functions along with some real-world problems such as beam designing model and Van der Waals’ equation of state are presented to ensure that the newly developed family efficiently competes with the other existing methods. The dynamical analysis of the proposed methods is also presented to validate the theoretical results by using graphical tools, termed as the basins of attraction.

Convergence Analysis of the Modified Chebyshev’s Method for Finding Multiple Roots

In this paper, an estimate of the radius of convergence ball of the modified Chebyshev’s method for finding multiple roots of nonlinear equations is provided under the hypotheses that the (m + 1)st derivative f(m+ 1) of function f is Holder continuous and bounded. The unique ball of a solution is also established. Finally, some examples are provided to show the effectiveness of our results.

A family of fifth-order iterative methods for finding multiple roots of nonlinear equations

A family of fifth-order iterative methods for finding multiple roots of nonlinear equations

Solving nonlinear equation systems via clustering-based adaptive speciation differential evolution.

In numerical computation, locating multiple roots of nonlinear equations (NESs) in a single run is a challenging work. In order to solve the problem of population grouping and parameters settings during the evolutionary, a clustering-based adaptive speciation differential evolution, referred to as CASDE, is presented to deal with NESs. CASDE offers three advantages: 1) the clustering with dynamic clustering sizes is used to set clustering sizes for different problems; 2) adaptive parameter control at the niche level is proposed to enhance the search ability and efficiency; 3) re-initialization mechanism motivates the algorithm to search new roots and saves computing resources. To evaluate the performance of CASDE, we select 30 problems with different features as test suite. Experimental results indicate that the speciation clustering with dynamic clustering sizes, niche adaptive parameter control, and re-initialization mechanism when combined together in a synergistic manner can improve the ability to find multiple roots in a single run. Additionally, our method is also compared with other state-of-the-art methods, which is capable of obtaining better results in terms of peak ratio and success rate. Finally, two practical mechanical problems are used to verify the performance of CASDE, and it also demonstrates superior results.

Optimal Methods for Finding Simple and Multiple Roots of Nonlinear Equations and their Basins of Attraction

In this paper, using the variant of Frontini-Sormani method, some higher order methods for finding the roots (simple and multiple) of nonlinear equations are proposed. In particular, we have constructed an optimal fourth order method and a family of sixth order method for finding a simple root. Further, an optimal fourth order method for finding a multiple root of a nonlinear equation is also proposed. We have used different weight functions to a cubically convergent For ntini-Sormani method for the construction of these methods. The proposed methods are tested on numerical examples and compare the results with some existing methods. Further, we have presented the basins of attraction of these methods to understand their dynamics visually.

One Parameter Optimal Derivative-Free Family to Find the Multiple Roots of Algebraic Nonlinear Equations

In this study, we construct the one parameter optimal derivative-free iterative family to find the multiple roots of an algebraic nonlinear function. Many researchers developed the higher order iterative techniques by the use of the new function evaluation or the first-order or second-order derivative of functions to evaluate the multiple roots of a nonlinear equation. However, the evaluation of the derivative at each iteration is a cumbersome task. With this motivation, we design the second-order family without the utilization of the derivative of a function and without the evaluation of the new function. The proposed family is optimal as it satisfies the convergence order of Kung and Traub’s conjecture. Here, we use one parameter a for the construction of the scheme, and for a=1, the modified Traub method is its a special case. The order of convergence is analyzed by Taylor’s series expansion. Further, the efficiency of the suggested family is explored with some numerical tests. The obtained results are found to be more efficient than earlier schemes. Moreover, the basin of attraction of the proposed and earlier schemes is also analyzed.

A Family of Derivative Free Optimal Fourth Order Methods for Computing Multiple Roots

Many optimal order multiple root techniques, which use derivatives in the algorithm, have been proposed in literature. But contrarily, derivative free optimal order techniques for multiple root are almost nonexistent. By this as an inspirational factor, here we present a family of optimal fourth order derivative-free techniques for computing multiple roots of nonlinear equations. At the beginning the convergence analysis is executed for particular values of multiplicity afterwards it concludes in general form. Behl et. al derivative-free method is seen as special case of the family. Moreover, the applicability and comparison is demonstrated on different nonlinear problems that certifies the efficient convergent nature of the new methods. Finally, we conclude that our new methods consume the lowest CPU time as compared to the existing ones. This illuminates the theoretical outcomes to a great extent of this study.

An Optimal Derivative-Free Ostrowski’s Scheme for Multiple Roots of Nonlinear Equations

Finding higher-order optimal derivative-free methods for multiple roots (m≥2) of nonlinear expressions is one of the most fascinating and difficult problems in the area of numerical analysis and Computational mathematics. In this study, we introduce a new fourth order optimal family of Ostrowski’s method without derivatives for multiple roots of nonlinear equations. Initially the convergence analysis is performed for particular values of multiple roots—afterwards it concludes in general form. Moreover, the applicability and comparison demonstrated on three real life problems (e.g., Continuous stirred tank reactor (CSTR), Plank’s radiation and Van der Waals equation of state) and two standard academic examples that contain the clustering of roots and higher-order multiplicity (m=100) problems, with existing methods. Finally, we observe from the computational results that our methods consume the lowest CPU timing as compared to the existing ones. This illustrates the theoretical outcomes to a great extent of this study.

General Local Convergence Theorems about the Picard Iteration in Arbitrary Normed Fields with Applications to Super–Halley Method for Multiple Polynomial Zeros

In this paper, we prove two general convergence theorems with error estimates that give sufficient conditions to guarantee the local convergence of the Picard iteration in arbitrary normed fields. Thus, we provide a unified approach for investigating the local convergence of Picard-type iterative methods for simple and multiple roots of nonlinear equations. As an application, we prove two new convergence theorems with a priori and a posteriori error estimates about the Super-Halley method for multiple polynomial zeros.

On Dynamics of Iterative Techniques for Nonlinear Equation with Applications in Engineering

In this article, we construct an optimal family of iterative methods for finding the single root and then extend this family for determining all the distinct as well as multiple roots of single-variable nonlinear equations simultaneously. Convergence analysis is presented for both the cases to show that the optimal order of convergence is 4 in the case of single root finding methods and 6 for simultaneous determination of all distinct as well as multiple roots of a nonlinear equation. The computational cost, basins of attraction, efficiency, log of residual, and numerical test examples show that the newly constructed methods are more efficient as compared to the existing methods in the literature.

A new two‐point scheme for multiple roots of nonlinear equations

In most of the earlier research for multiple zeros, in order to obtain a new iteration function from the existing scheme, the usual practice is to make no change at the first substep. In this paper, we explore the idea that what are the advantages if the flexibility of choice is also given at the first substep. Therefore, we present a new two‐point sixth‐order scheme for multiple roots (m>1). The main advantages of our scheme over the existing schemes are flexibility at both substeps, simple body structure, smaller residual error, smaller error difference between two consecutive iterations, and smaller asymptotic error constant. The development of the scheme is based on midpoint formula and weight functions of two variables. We compare our methods with the existing methods of the same order with real‐life applications as well as standard test problems. From the numerical results, we find that our methods can be considered as better alternates for the existing methods of the same order. Finally, dynamical study of the proposed schemes is presented that confirms the theoretical results.