Computational and Applied Mathematics最新文献

This paper introduces two new identification methods for linear quadratic (LQ) ordinal potential differential games (OPDGs). Potential games are notable for their benefits, such as the computability and guaranteed existence of Nash Equilibria. While previous research has analyzed ordinal potential static games, their applicability to various engineering applications remains limited. Despite the earlier introduction of OPDGs, a systematic method for identifying a potential game for a given LQ differential game has not yet been developed. To address this gap, we propose two identification methods to provide the quadratic potential cost function for a given LQ differential game. Both methods are based on linear matrix inequalities (LMIs). The first method aims to minimize the condition number of the potential cost function’s parameters, offering a faster and more precise technique compared to earlier solutions. In addition, we present an evaluation of the feasibility of the structural requirements of the system. The second method, with a less rigid formulation, can identify LQ OPDGs in cases where the first method fails. These novel identification methods are verified through simulations, demonstrating their advantages and potential in designing and analyzing cooperative control systems.

In this study, we explore the valuation challenge posed by American options subject to regime switching, utilizing a model defined by a complex system of parabolic variational inequalities within an infinite domain. The initial pricing model is transformed into a linear complementarity problem (LCP) in a bounded rectangular domain, achieved through the application of a priori estimations and the introduction of an appropriate artificial boundary condition. To discretize the LCP, we employ a finite difference method (FDM), and address the resulting discretized system using a primal-dual active set (PDAS) strategy. The PDAS approach is particularly advantageous for its ability to concurrently determine the option’s price and the optimal exercise boundary. This paper conducts an extensive convergence analysis, evaluating both the truncation error associated with the FDM and the iteration error of the PDAS. Comprehensive numerical simulations are performed to validate the method’s accuracy and efficiency, underscoring its significant potential for application in the field of financial mathematics.

In this paper, we obtain a new estimate for the (product) (gamma )-diagonally dominant degree of the Schur complement of matrices. As applications we discuss the localization of eigenvalues of the Schur complement and present several upper and lower bounds for the determinant of strictly (gamma )-diagonally dominant matrices, which generalizes the corresponding results of Liu and Zhang (SIAM J. Matrix Anal. Appl. 27 (2005) 665-674).

In this article, we discuss sustainable harvesting using a Filippov predator–prey system, which can produce yield and at the same time prevent over-exploitation of bioresources. The model is composed of two subsystems and the dynamics switch from one to the other with the help of a switching condition. We have derived possible equilibria, their existence and stability conditions for the respective subsystems, along with a comprehensive analysis of their phase space. The local and global stability analysis of the two subsystems, with and without harvesting, are studied. Furthermore, for the Filippov system, we have performed bifurcation analysis for several key parameters like predation rate, threshold quantity and prey refuge. Some local and global sliding bifurcations are also observed for the system. The system is shown to have multiple stable steady states or multiple stable sliding cycles for some suitable choice of parameters. Numerical simulations are presented to illustrate the dynamical behaviour of the system.

In this paper, we deal with some shape optimization geometrical inverse spectral problems involving the first eigenvalue and eigenfunction of a p-Laplace operator, over a class of open domains with prescribed volume. We first briefly show the existence of the optimal shape design for the (L^p) norm of the eigenfunctions. We carried out the shape derivative calculation of this shape optimization problem using deformation of domains by vector fields. Then we propose a numerical method using lagrangian functional, Hadamard’s shape derivative and gradient method to determine the minimizers for this shape optimization problem. We investigate also numerically the problem of minimizing the first eigenvalue of the p-Laplacian-Dirichlet operator with volume-constraint on domains, using constrained and unconstrained shape optimization formulations. The resulting proposed algorithms of the optimization process are based on the inverse power algorithm (Biezuner et al. 2012) and the finite elements method performed to approximate the first eigenvalue and related eigenfunction. Numerical examples and illustrations are provided for different constrained and unconstrained shape optimization formulations and for various cost functionals to show the efficiency and practical suitability of the proposed approach.

Several sharp approximations of the generalized-binomial-coefficient function having real arguments are presented on the basis of Stirling’s approximation formula for (Gamma ) function.

To further accelerate the convergence rate of the recent proposed modified modulus-based matrix splitting (MMMS) iteration method for solving the implicit complementarity problems, by using the two-step iteration methodology, a class of modified two-step modulus-based matrix splitting (MTMMS) iteration methods are studied in this paper. The convergence analyses of the MTMMS iteration method are carefully studied when the system matrix is a positive definite matrix or an (H_+)-matrix. Finally, two numerical experiments are presented. Numerical results show that the proposed MTMMS iteration method performs much better than the existing MMMS iteration method.

In this work, we propose a piecewise Jacobi–Gauss spectral collocation (JGSC) method for simulating a multi-particle system involving processing delay. Through the use of Jacobi orthogonal approximation and simple Picard iteration, the method obtains the Jacobi series solution of the multi-particle model, allowing us to derive the numerical solution of the processing delay directly. The matrix–vector form of the method helps to obtain the solution parallelly and improves the efficiency significantly. Additionally, the eigenvalues of the iteration’s coefficient matrix are evaluated in order to analyze the convergence of the JGSC method numerically. Numerical experiments illustrate that the JGSC method can keep the high accuracy and efficiency. Furthermore, simulation results of the model indicate that the flocking behavior can only achieved with small enough processing time delays and large enough sizes of the neighborhood.

The triangle-degree of a vertex v of a simple graph G is the number of triangles in G that contain v. A simple graph is triangle-distinct if all its vertices have distinct triangle-degrees. Berikkyzy et al. [Discrete Math. 347 (2024) 113695] recently asked whether there exists a regular graph that is triangle-distinct. Here we first showcase the examples of regular, triangle-distinct graphs, and then show that for every natural number k there exists a family of (2^k) regular triangle-distinct graphs, all having the same order and size.

In this paper, a different approach is used to define a cartesian product on soft sets. This method processes both alternatives and parameters. The notion of the cartesian product is then used to define the idea of a soft relation. The concepts of reflexion, symmetry and transition are defined on the soft relation. Some properties are investigated. Also, the soft function notion is introduced. Various instances are provided as the key characteristics of the structures that are being presented are analyzed. Finally, an application is presented by building a decision making algorithm on the soft relation.