this study focuses on the optimization of the plane structure. sequential quadratic programming (sqp) will be utilized, which is one of the most efficient methods for solving nonlinearly constrained optimization problems. a new formulation for the second order sensitivity analysis of the two-dimensional finite element will be developed. all the second order required derivatives will be calculat...

Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by ...

In this paper, a new numerical method for solving fractional optimal control problems (FOCPs) is presented. The fractional derivative in the dynamic system is described in the Caputo sense. The method is based upon biorthogonal cubic Hermite spline multiwavelets approximations. The properties of biorthogonal multiwavelets are first given. The operational matrix of fractional Riemann-Lioville in...

This paper presents a canonical dual approach for minimizing a sum of quadratic function and a ratio of nonconvex functions in R. By introducing a parameter, the problem is first equivalently reformed as a nonconvex polynomial minimization with elliptic constraint. It is proved that under certain conditions, the canonical dual is a concave maximization problem in R that exhibits no duality gap....

Energy efficiency (EE) is an important aspect of satellite communications. Different with the existing algorithms that typically use first-order Taylor lower bound approximation to convert non-convex EE maximization (EEM) problems into convex ones, in this letter a two-step quadratic transformation method presented. In first step, fractional form achievable rate over total power consumption con...

We propose a class of quadratic optimization problems whose exact optimal objective values can be computed by their completely positive cone programming relaxations. The objective function can be any quadratic form. The constraints of each problem are described in terms of quadratic forms with no linear terms, and all constraints are homogeneous equalities, except one inhomogeneous equality whe...

We propose a class of quadratic optimization problems whose exact optimal objective values can be computed by their completely positive cone programming relaxations. The objective function can be any quadratic form. The constraints of each problem are described in terms of quadratic forms with no linear terms, and all constraints are homogeneous equalities, except one inhomogeneous equality whe...

In this paper, we considered a Stochastic Interval-Valued Linear Fractional Programming problem(SIVLFP). In this problem, the coefficients and scalars in the objective function are fractional-interval, and technological coefficients and the quantities on the right side of the constraints were random variables with the specific distribution. Here we changed a Stochastic Interval-Valued Fractiona...

The theory of differential and integral equations of fractional order has recently received a lot of attention and now constitutes a significant branch of nonlinear analysis. Numerous research papers and monographs have appeared devoted to differential and integral equations of fractional order cf., e.g., 1–6 . These papers contain various types of existence results for equations of fractional ...