Skip to Main content Skip to Navigation
Journal articles

Reduced quasi-Newton method for simultaneous design and optimization

Abstract : We consider the task of design optimization where the constraint is a state equation that can only be solved by a typically rather slowly converging fixed point solver. This process can be augmented by a corresponding adjoint solver and based on the resulting approximate reduced derivatives also an optimization iteration which actually changes the design. To coordinate the three iterative processes, we use an exact penalty function of doubly augmented Lagrangian type. The main issue here is how to derive a design space preconditioner for the approximated reduced gradient which ensures a consistent reduction of the employed penalty function as well as significant design corrections. Some numerical experiments for an alternating approach where any combination and sequencing of steps are used to improve feasibility and optimality done on a variant of the Bratu problem are presented.
Complete list of metadata
Contributor : Adel Hamdi Connect in order to contact the contributor
Submitted on : Wednesday, January 1, 2020 - 2:46:01 PM
Last modification on : Wednesday, March 2, 2022 - 9:42:12 AM

Links full text



Adel Hamdi, Andreas Griewank. Reduced quasi-Newton method for simultaneous design and optimization. Computational Optimization and Applications, Springer Verlag, 2011, 49 (3), pp.521-548. ⟨10.1007/s10589-009-9306-x⟩. ⟨hal-02426065⟩



Record views