In this paper, the researchers present a multi-objective linear fractional inventory model using fuzzy pro-gramming. The proposed method in this paper is applied to a problem with two objective functions. The re-sulted fuzzy model is transformed into an ordinary linear programming. The implementation of the develop-ing model presented in this paper is demonstrated through the use of some numeri...

In this paper, the Chebyshev spectral collocation method(CSCM) for one-dimensional linear hyperbolic telegraph equation is presented. Chebyshev spectral collocation method have become very useful in providing highly accurate solutions to partial differential equations. A straightforward implementation of these methods involves the use of spectral differentiation matrices. Firstly, we transform ...

By applying finite difference formula to time discretization and the cubic B-splines for spatial variable, a numerical method for solving the inverse system of Burgers equations is presented. Also, the convergence analysis and stability for this problem are investigated and the order of convergence is obtained. By using two test problems, the accuracy of presented method is verified. Additional...

This article is devoted to an approach solving a problem of the efficiency parallel computing. The theoretical basis this concept Q -determinant. Any numerical algorithm has -determinant clear structure and convenient for implementation. consists -terms. Their number equal output data items. Each -term describes all possible ways compute one items based on input data. We also describe software ...

This paper presents a practical and efficient method to solve large-scale nonlinear equations. The global convergence of this new trust region algorithm is verified. The algorithm is then used to solve the nonlinear equations arising in an Expanded Lagrangian Function (ELF). Numerical results for the implementation of some large-scale problems indicate that the algorithm is efficient for these ...

Numerical experiences show that bundle methods are very efficient for solving convex non-smooth optimization problems. In this paper we describe briefly the mathematical background of a bundle method and discuss practical aspects for the numerical implementation. Further, we give a detailed documentation of our implementation and report about numerical tests.