This paper is concerned with some feasibility issues in mathematical programs with equilibrium constraints (MPECs) where additional joint constraints are present that must be satis ed by the state and design variables of the problems. We introduce su cient conditions that guarantee the feasibility of these MPECs. It turns out that these conditions also guarantee the feasibility of the quadratic...

The optimal boundary control of Navier–Stokes flow is formulated as a constrained optimization problem and a sequential quadratic programming (SQP) approach is studied for its solution. Since SQP methods treat states and controls as independent variables and do not insist on satisfying the constraints during the iterations, care must be taken to avoid a possible incompatibility of Dirichlet bou...

The aim of the paper is to provide a theoretical basis for approximate reduced SQP methods. In contrast to inexact reduced SQP methods, the forward and the adjoint problem accuracies are not increased when zooming in to the solution of an optimization problem. Only linear-quadratic problems are treated, where approximate reduced SQP methods can be viewed as null-space iterations for KKT systems...

this paper presents a fuzzy approach to the prediction of highly nonlinear timeseries.the optimized mamdani-type fuzzy system denoted sqp-flc is applied forthe input-output modeling of measured data. in order to tune fuzzy membershipfunctions, a sequential quadratic programming (sqp) method is employed. theproposed method is evaluated and validated on a highly complex time series, dailygold pri...

Regularized and stabilized sequential quadratic programming methods are two classes of sequential quadratic programming (SQP) methods designed to resolve the numerical and theoretical difficulties associated with ill-posed or degenerate nonlinear optimization problems. Recently, a regularized SQP method has been proposed that provides a strong connection between augmented Lagrangian methods and...

Due to many classical identification methods cannot be directly used for closed-loop control system, an improved identification method is proposed to simultaneously identify model parameters and the structure. The improved identification method used the genetic algorithm to estimate the initial search scope for the PSO algorithm, and then used the search result as the initial value of the Rosen...

Semilinear elliptic optimal control problems with pointwise control and mixed control-state constraints are considered. Necessary and sufficient optimality conditions are given. The equivalence of the SQP method and Newton’s method for a generalized equation is discussed. Local quadratic convergence of the SQP method is proved.

Multiple-input multiple-output (MIMO) detection is a fundamental problem in wireless communications and it strongly NP-hard general. Massive MIMO has been recognized as key technology the fifth generation (5G) beyond communication networks, which on one hand can significantly improve performance, other poses new challenges of solving corresponding optimization problems due to large size. While ...

An SQP algorithm is presented for solving constrained nonlinear programming problems. The algorithm uses three stepsize strategies in order to achieve global and superlinear convergence. Switching rules are implemented that combine the merits and avoid the drawbacks of the three stepsize strategies. A penalty parameter is determined using an adaptive strategy that aims to achieve sufficient dec...