# A derivative-free trust-region augmented Lagrangian algorithm

@inproceedings{Audet2016ADT, title={A derivative-free trust-region augmented Lagrangian algorithm}, author={Charles Audet and S{\'e}bastien Le Digabel and Mathilde Peyrega}, year={2016} }

We present a new derivative-free trust-region (DFTR) algorithm to solve general nonlinear constrained problems with the use of an augmented Lagrangian method. No derivatives are used, neither for the objective function nor for the constraints. An augmented Lagrangian method, known as an effective tool to solve equality and inequality constrained optimization problems with derivatives, is exploited to minimize the subproblems, composed of quadratic models that approximate the original objective…

## 2 Citations

### Efficient solution of quadratically constrained quadratic subproblems within the mesh adaptive direct search algorithm

- Computer ScienceEur. J. Oper. Res.
- 2018

### Efficient solution of quadratically constrained quadratic subproblems within the MADS algorithm ∗

- Computer Science
- 2016

This work explores different algorithms that exploit the structure of the quadratic models: the first one applies an l1 exact penalty function, the second uses an augmented Lagrangian and the third one combines the former two, resulting in a new algorithm.

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