Most local convergence analyses of the sequential quadratic programming (SQP) algorithm for nonlinear programming make strong assumptions about the solution, namely, that the active constraint gradients are linearly independent and that there are no weakly active constraints. In this paper, we establish a framework for variants of SQP that retain the characteristic superlinear convergence rate ...

Muscle forces during locomotion are often predicted using static optimisation and SQP. SQP has been criticised for over-estimating force magnitudes and under-estimating co-contraction. These problems may be related to SQP's difficulty in locating the global minimum to complex optimisation problems. Algorithms designed to locate the global minimum may be useful in addressing these problems. Musc...

Successive Quadratic Programming (SQP) has been the method of choice for the solution of many nonlinear programming problems in process engineering. However, for the solution of large problems with SQP based codes, the combinatorial complexity associated with active set quadratic programming (QP) methods can be a bottleneck in exploiting the problem structure. In this paper, we examine the meri...

This paper presents hybrid differential evolution DE and sequential quadratic programming SQP for solving the dynamic economic dispatch DED problem for generating units with valvepoint effects. DE is used as a global optimizer and SQP is used as a fine tuning to determine the optimal solution at the final. The feasibility of the proposed method is validated with fiveand ten-unit test systems. R...

We consider the inexact restoration and the composite-step sequential quadratic programming (SQP) methods, and relate them to the so-called perturbed SQP framework. In particular, iterations of the methods in question are interpreted as certain structured perturbations of the basic SQP iterations. This gives a different insight into local behaviour of those algorithms, as well as improved or di...

Recently, nonlinear programming solvers have been used to solve a range of mathematical programs with equilibrium constraints (MPECs). In particular, sequential quadratic programming (SQP) methods have been very successful. This paper examines the local convergence properties of SQP methods applied to MPECs. SQP is shown to converge superlinearly under reasonable assumptions near a strongly sta...