Abstract:In this manuscript, a new parametric class of iterative methods for solving nonlinear systems of equations is proposed. Its fourth-order of convergence is proved and a dynamical analysis on low-degree polynomials is made in order to choose those elements of the family with better conditions of stability. These results are checked by solving the nonlinear system that arises from the partial differential equation of molecular interaction.
“…Now, using the values from (6), (12), (13), (21), and (22) in (18), the error equation of the method is…”
Section: Optimal Eighth Order Methodsmentioning
confidence: 99%
“…Dynamics of a rational operator give important information about the convergence, efficiency and stability of the iterative methods. During the last few decades, many researchers, e.g., [10][11][12][13][14][15][16] and references therein, study the dynamical behavior of rational operators associated with iterative methods. Furthermore, there is an extensive literature [17][18][19][20][21] to understand and implement further results on the dynamics of rational functions.…”
In this paper, using the idea of weight functions on the Potra–Pták method, an optimal fourth order method, a non optimal sixth order method, and a family of optimal eighth order methods are proposed. These methods are tested on some numerical examples, and the results are compared with some known methods of the corresponding order. It is proved that the results obtained from the proposed methods are compatible with other methods. The proposed methods are tested on some problems related to engineering and science. Furthermore, applying these methods on quadratic and cubic polynomials, their stability is analyzed by means of their basins of attraction.
“…Now, using the values from (6), (12), (13), (21), and (22) in (18), the error equation of the method is…”
Section: Optimal Eighth Order Methodsmentioning
confidence: 99%
“…Dynamics of a rational operator give important information about the convergence, efficiency and stability of the iterative methods. During the last few decades, many researchers, e.g., [10][11][12][13][14][15][16] and references therein, study the dynamical behavior of rational operators associated with iterative methods. Furthermore, there is an extensive literature [17][18][19][20][21] to understand and implement further results on the dynamics of rational functions.…”
In this paper, using the idea of weight functions on the Potra–Pták method, an optimal fourth order method, a non optimal sixth order method, and a family of optimal eighth order methods are proposed. These methods are tested on some numerical examples, and the results are compared with some known methods of the corresponding order. It is proved that the results obtained from the proposed methods are compatible with other methods. The proposed methods are tested on some problems related to engineering and science. Furthermore, applying these methods on quadratic and cubic polynomials, their stability is analyzed by means of their basins of attraction.
“…The objective function (2) states that the distance traveled and number of vehicles should be minimized, M being a sufficiently large constant. (3) ensures that one and only one node can be visited after an order.…”
Section: Mathematical Formulationmentioning
confidence: 99%
“…A vast number of problems from Applied Science including engineering can be brought by means of solving a nonlinear equation using mathematical modeling [1][2][3]. One of that problems, in concrete the capillary transport of goods problem, is studied in this paper.…”
a b s t r a c tThis paper presents a novel optimization algorithm that consists of metaheuristic processes to solve the problem of the capillary distribution of goods in major urban areas taking into consideration the features encountered in real life: time windows, capacity constraints, compatibility between orders and vehicles, maximum number of orders per vehicle, orders that depend on the pickup and delivery and not returning to the depot. With the intention of reducing the wide variety of constraints and complexities, known as the Rich Vehicle Routing Problem, this algorithm proposes feasible alternatives in order to achieve the main objective of this research work: the reduction of costs by minimizing distances and reducing the number of vehicles used as long as the service quality to customers is optimum and a load balance among vehicles is maintained.
“…The idea of using basins of attraction was initiated by Stewart [27] and followed by the works of Amat et al [28][29][30], and [31], Scott et al [32], Chun et al [33,40], Magreňán [34], Argyros et al [35], Chicharro et al [37], and Cordero et al [36,38]. The only papers comparing basins of attraction for methods to obtain multiple roots are due to Neta et al [41], Neta and Chun [18], [42], and Chun and Neta [26].…”
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