This paper addresses the need for nonlinear programming algorithms that provide fast local convergence guarantees no matter if a problem is feasible or infeasible. We present an a...
Abstract. Sequential quadratic programming (SQP) methods have proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective...
Philip E. Gill, Walter Murray, Michael A. Saunders
Mathematical programs with nonlinear complementarity constraints are reformulated using better-posed but nonsmooth constraints. We introduce a class of functions, parameterized by...
We present an adaptive multilevel generalized SQP method to solve PDAE-constrained optimization problems. It explicitly allows the use of independent integration schemes such that...
Debora Clever, Jens Lang, Stefan Ulbrich, J. Carst...
Abstract. Sequential quadratic programming (SQP) methods form a class of highly efficient algorithms for solving nonlinearly constrained optimization problems. Although second deri...