Global convergence on an active set SQP for inequality constrained optimization
Copyright policy )Global convergence on an active set SQP for inequality constrained optimization
The author presents and studies an active set sequential quadratic programming (SQP) algorithm for inequality constrained optimization problems of the form \[ \min f(x)\quad\text{s.t. }c(x)\geq 0, \] where \(f(x)\) and \(c(x)\) are twice continuously differentiable functions. The given results show that the global convergence of the SQP algorithm is still guaranteed by deleting some redundant constraints. No numerical tests are given.
- National University of Singapore Singapore
- National University of Singapore Libraries Singapore
- Nationl University of Singapore Singapore
- Singapore-MIT Alliance Singapore
- Hebei University of Technology China (People's Republic of)
Applied Mathematics, Sequential quadratic programming, active set method, 510, Methods of successive quadratic programming type, global convergence, Computational Mathematics, Numerical mathematical programming methods, Nonlinear programming, Nonlinearly constrained optimization, Active set
Applied Mathematics, Sequential quadratic programming, active set method, 510, Methods of successive quadratic programming type, global convergence, Computational Mathematics, Numerical mathematical programming methods, Nonlinear programming, Nonlinearly constrained optimization, Active set
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