Algorithms based on the sequential quadratic programming (SQP) approach are among the most effective methods for solving (1). Some interesting algorithms of this class are given, for example, in [3, 4 ...

A sequential quadratic programming (SQP) method is presented that aims to overcome some of the drawbacks of contemporary SQP methods. It avoids the difficulties associated with indefinite quadratic ...

A SQP algorithm implementation for solving nonlinear constrained optimization problems - spiroskou/Sequential-Quadratic-Programming-method-Implementation-in-Matlab. Skip to content. Navigation Menu ...

Python implementation of a primal active set method for sequential quadratic programming. A base ActiveSet class implements the generic form of the algorithm while derived classes implement the small ...

J. L. Morales, J. Nocedal and Y. Wu, “A Sequential Quadratic Programming Algorithm with an Additional Equality Constrained Phase,” IMA Journal of Numerical Analysis, Vol. 32, No. 2, 2012, ... Improved ...

A novel approach to exploiting the log-convex structure present in many design problems is developed by modifying the classical Sequential Quadratic Programming (SQP) algorithm. The modified algorithm ...

We review the motivation for, the current state-of-the-art in convergence results, and some open questions concerning the stabilized version of the sequential quadratic programming algorithm for ...