Sequential Quadratic Programming
- 1 January 1995
- journal article
- research article
- Published by Cambridge University Press (CUP) in Acta Numerica
- Vol. 4, 1-51
- https://doi.org/10.1017/s0962492900002518
Abstract
Since its popularization in the late 1970s, Sequential Quadratic Programming (SQP) has arguably become the most successful method for solving nonlinearly constrained optimization problems. As with most optimization methods, SQP is not a single algorithm, but rather a conceptual method from which numerous specific algorithms have evolved. Backed by a solid theoretical and computational foundation, both commercial and public-domain SQP algorithms have been developed and used to solve a remarkably large set of important practical problems. Recently large-scale versions have been devised and tested with promising results.Keywords
This publication has 63 references indexed in Scilit:
- Theory of algorithms for unconstrained optimizationActa Numerica, 1992
- On Secant Updates for Use in General Constrained OptimizationMathematics of Computation, 1988
- On secant updates for use in general constrained optimizationMathematics of Computation, 1988
- Numerical Methods for Unconstrained Optimization and Nonlinear Equations.Journal of the American Statistical Association, 1985
- The convergence of matrices generated by rank-2 methods from the restricted ?-class of BroydenNumerische Mathematik, 1984
- The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search functionNumerische Mathematik, 1982
- The watchdog technique for forcing convergence in algorithms for constrained optimizationPublished by Springer Nature ,1982
- Augmented Lagrangians which are quadratic in the multiplierJournal of Optimization Theory and Applications, 1980
- On the Local and Superlinear Convergence of Quasi-Newton MethodsIMA Journal of Applied Mathematics, 1973
- Iterative Solution of Nonlinear Equations in Several VariablesMathematics of Computation, 1971