We discuss the integration of a sequential quadratic programming (SQP) method with an optimization-level domain decomposition (DD) preconditioner for the solution of the quadratic optimization subproblems. The DD method is an extension of the well-known Neumann-Neumann method to the optimization context and is based on a decomposition of the first order system of optimality conditions. The SQP ...

NE/SQP is a recent algorithm tha t has proven quite effective for solving the pure and mixed forms of the nonlinear complementarity problem (NCP). NE/SQP is robust in the sense that i ts direction-finding subproblems are always solvable; in addition, the convergence rate of this method is Q-quadratic. In this paper we consider a generalized version of NE/SQP proposed by Pang and Qi, that is sui...

NE/SQP is a recent algorithm that has proven quite eeective for solving the pure and mixed forms of the nonlinear complementarity problem (NCP). NE/SQP is robust in the sense that its direction-nding subproblems are always solvable; in addition, the convergence rate of this method is Q-quadratic. In this paper we consider a generalized version of NE/SQP proposed by Pang and Qi, that is suitable...

We consider sequential quadratic programming (SQP) methods applied to optimization problems with nonlinear equality constraints and simple bounds. In particular, we propose and analyze a truncated SQP algorithm in which subproblems are solved approximately by an infeasible predictor-corrector interior-point method, followed by setting to zero some variables and some multipliers so that compleme...

A hybrid algorithm by integrating an improved particle swarm optimization (IPSO) with successive quadratic programming (SQP), namely IPSO–SQP, is proposed for solving nonlinear optimal control problems. The particle swarm optimization (PSO) is showed to converge rapidly to a near optimum solution, but the search process will become very slow around global optimum. On the contrary, the ability o...

The field of constrained nonlinear programming (NLP) has been principally challenging to various gradient based optimization techniques. The Sequential quadratic programming algorithm (SQP) that uses active set strategy in solving quadratic programming (QP) subproblems proves to be efficient in locating the points of local optima. However, its efficient determination of the optimal active set h...