Sequential quadratic programming methods for nonlinear programming. (English) Zbl 0551.90079
Computer aided analysis and optimization of mechanical system dynamics, Proc. NATO Adv. Study Inst., Iowa City/USA 1983, NATO ASI Ser., Ser. F 9, 679-700 (1984).
[For the entire collection see Zbl 0544.00026.]
Sequential quadratic programming (SQP) methods are among the most effective techniques known today for solving nonlinearly constrained optimization problems. This paper presents an overview of SQP methods based on a quasi-Newton approximation to the Hessian of the Lagrangian function (or an augmented Lagrangian function). We briefly describe some of the issues in the formulation of SQP methods, including the form of the subproblem and the choice of merit function. We conclude with a list of available SQP software.
Sequential quadratic programming (SQP) methods are among the most effective techniques known today for solving nonlinearly constrained optimization problems. This paper presents an overview of SQP methods based on a quasi-Newton approximation to the Hessian of the Lagrangian function (or an augmented Lagrangian function). We briefly describe some of the issues in the formulation of SQP methods, including the form of the subproblem and the choice of merit function. We conclude with a list of available SQP software.
MSC:
| 90C30 | Nonlinear programming |
| 49M37 | Numerical methods based on nonlinear programming |
| 65K05 | Numerical mathematical programming methods |
| 90C20 | Quadratic programming |
