A Multidimensional Bisection Method for Unconstrained Minimization Problem
نویسنده
چکیده
An extension of a new multidimensional bisection method for minimizing function over simplex is proposed for solving nonlinear unconstrained minimization problem. The method does not require a differentiability of function, and is guaranteed to converge to the minimizer for the class of strictly unimodal functions. The computational results demonstrating an effectiveness of algorithm for minimizing nonsmooth functions are presented.
منابع مشابه
A Multidimensional Bisection Method for Minimizing Function over Simplex
A new method for minimization problem over simplex, as a generalization of a well-known in onedimensional optimization bisection method is proposed. The convergence of the method for class of strictly unimodal functions including class of strictly convex functions is proved. The computational results are presented for a set of test problems.
متن کاملA Neural Network Method Based on Mittag-Leffler Function for Solving a Class of Fractional Optimal Control Problems
In this paper, a computational intelligence method is used for the solution of fractional optimal control problems (FOCP)'s with equality and inequality constraints. According to the Ponteryagin minimum principle (PMP) for FOCP with fractional derivative in the Riemann- Liouville sense and by constructing a suitable error function, we define an unconstrained minimization problem. In the optimiz...
متن کاملMinimization of Frequency-Weighted l2 -Sensitivity Subject to l2 -Scaling Constraints for Two-Dimensional State-Space Digital Filters
This paper investigates the problem of frequencyweighted l2-sensitivity minimization subject to l2-scaling constraints for two-dimensional (2-D) state-space digital filters described by the Roesser model. It is shown that the FornasiniMarchesini second model can be imbedded in the Roesser model. Two iterative methods are developed to solve the constrained optimization problem encountered. The f...
متن کاملSDO relaxation approach to fractional quadratic minimization with one quadratic constraint
In this paper, we study the problem of minimizing the ratio of two quadratic functions subject to a quadratic constraint. First we introduce a parametric equivalent of the problem. Then a bisection and a generalized Newton-based method algorithms are presented to solve it. In order to solve the quadratically constrained quadratic minimization problem within both algorithms, a semidefinite optim...
متن کاملA NEW APPROACH TO THE SOLUTION OF SENSITIVITY MINIMIZATION IN LINEAR STATE FEEDBACK CONTROL
In this paper, it is shown that by exploiting the explicit parametric state feedback solution, it is feasible to obtain the ultimate solution to minimum sensitivity problem. A numerical algorithm for construction of a robust state feedback in eigenvalue assignment problem for a controllable linear system is presented. By using a generalized parametric vector companion form, the problem of eigen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2008