In this paper, we propose the new concept of optimal solution for fuzzy variational problems based on the possibility and necessity measures. Inspired by the well–known embedding theorem, we can transform the fuzzy variational problem into a bi–objective variational problem. Then the optimal solutions of fuzzy variational problem can be obtained by solving its corresponding biobjective variatio...

We consider a variational problem for the two-dimensional (2D) Heisenberg and XY models, using a trial state which is constructed as a 2D product of local weights. Variational energy is calculated by use of the the corner transfer matrix renormalization group (CTMRG) method, and its upper bound is surveyed. The variational approach is a way of applying the density matrix renormalization group m...

a numerical method for solving variational problems is presented in this paper. the method is based upon hybrid of hartley functions approximations. the properties of hybrid functions which are the combinations of block-pulse functions and hartley functions are first presented. the operational matrix of integration is then utilized to reduce the variational problems to the solution of algebraic...

Variational quantum algorithms are one of the most promising methods that can be implemented on noisy intermediate-scale (NISQ) machines to achieve a advantage over classical computers. This article describes use variational algorithm in conjunction with finite difference method for calculation propagation modes an electromagnetic wave hollow metallic waveguide. The two-dimensional (2D) wavegui...

this paper presents an efficient modification of the variational iteration method for solvingboundary value problems using the chebyshev polynomials. the proposed method can be applied to linearand nonlinear models. the scheme is tested for some examples and the obtained results demonstrate thereliability and efficiency of the proposed method.

we establish a relationship between general constrained pseudoconvex optimization problems and globally projected dynamical systems. a corresponding novel neural network model, which is globally convergent and stable in the sense of lyapunov, is proposed. both theoretical and numerical approaches are considered. numerical simulations for three constrained nonlinear optimization problems are giv...

we introduce variational inequality problems on hilbert $c^*$-modules and we prove several existence results for variational inequalities defined on closed convex sets. then relation between variational inequalities, $c^*$-valued metric projection and fixed point theory  on  hilbert $c^*$-modules is studied.

We introduce a reconstruction framework that can account for shape related a priori information in ill-posed linear inverse problems in imaging. It is a variational scheme that uses a shape functional defined using deformable templates machinery from shape theory. As proof of concept, we apply the proposed shape based reconstruction to 2D tomography with very sparse measurements, and demonstrat...

In this paper, some properties of  pseudoinvex functions, defined by means of  limiting subdifferential, are discussed. Furthermore, the Minty vector variational-like inequality,  the Stampacchia vector variational-like inequality, and the  weak formulations of these two inequalities  defined by means of limiting subdifferential are studied. Moreover, some relationships  between the vector vari...

Micro Abstract We present a new and completely parallel approach for fluid-structure interaction, which includes also contact between the elastic structures. Our approach is inspired by the fictitious domain method and makes intensive use of variational transfer between the solid and the fluid and on the possibly contacting surfaces between solids. We present the discretization, the setup of th...