Line search algorithms for nonlinear programming must include safeguards to enjoy global convergence properties. This paper describes an exact penalization approach that extends the class of problems that can be solved with line search SQP methods. In the new algorithm, the penalty parameter is adjusted at every iteration to ensure sufficient progress in linear feasibility and to promote accept...

This paper presents an active-set algorithm for large-scale optimization that occupies the middle ground between sequential quadratic programming (SQP) and sequential linear-quadratic programming (SL-QP) methods. It consists of two phases. The algorithm first minimizes a piecewise linear approximation of the Lagrangian, subject to a linearization of the constraints, to determine a working set. ...

This paper describes an adaptive algorithm for optimal control of time-dependent partial di erentialalgebraic equation (PDAE) systems. A direct method based on a modi ed multiple shooting type technique and sequential quadratic programming (SQP) is used for solving the optimal control problem, while an adaptive mesh re nement (AMR) algorithm is employed to dynamically adapt the spatial integrat...

A technique for maintaining the positive definiteness of the matrices in the quasi-Newton version of the SQP algorithm is proposed. In our algorithm, matrices approximating the Hessian of the augmented Lagrangian are updated. The positive definiteness of these matrices in the space tangent to the constraint manifold is ensured by a so-called piecewise line-search technique, while their positive...

Sequential quadratic programming (SQP) methods for the optimal control of the instationary Navier-Stokes equations with pointwise constraints on the control are considered. Due to the presence of the constraints the quadratic subproblems (QP) of SQP require a more sophisticated solver compared to the unconstrained case. In this paper, a semismooth Newton method is proposed for efficiently solvi...

In [19], we gave global convergence results for a second-derivative SQP method for minimizing the exact l1-merit function for a fixed value of the penalty parameter. To establish this result, we used the properties of the so-called Cauchy step, which was itself computed from the so-called predictor step. In addition, we allowed for the computation of a variety of (optional) SQP steps that were ...

In this paper a hybrid scheme using GA and SQP method is introduced. In the hybrid GA-SQP the role of the GA is to explore the search place in order to either isolate the most promising region of the search space. The role of the SQP is to exploit the information gathered by the GA. To demonstrate the usefulness of the presented approach, two cases for parameter identification of different comp...

The development and implementation of the Range and Null space Decomposition (RND) strategy for large-scale problems is described with emphasis on the optimization of engineering systems. The RND technique, as detailed in Vasantharajan and Biegler (1988), uses nonorthonormal, gradient based projections for the Jacobian. However, this implementation is dense, and does not take advantage of syste...

Product reuse and recovery is an efficient tool that helps companies to simultaneously address economic environmental dimensions of sustainability. This paper presents a novel problem for stock management reusable products in single-vendor, multi-product, multi-retailer network. Several constraints, such as the maximum budget, storage capacity, number orders, etc., are considered their stochast...

For an optimization problem with general equality and inequality constraints, we propose an algorithm which uses subproblems of the stabilized SQP (sSQP) type for approximately solving subproblems of the augmented Lagrangian method. The motivation is to take advantage of the well-known robust behavior of the augmented Lagrangian algorithm, including on problems with degenerate constraints, and ...