G-2016-45
Efficient solution of quadratically constrained quadratic subproblems within a direct-search algorithm
Nadir Amaioua, Charles Audet, Andrew R. Conn et Sébastien Le Digabel
The Mesh Adaptive Direct Search algorithm (MADS) is an iterative method for constrained blackbox optimization problems.
One of the optional MADS features is a versatile search step in which quadratic models are built leading to a series of quadratically constrained quadratic subproblems.
This work explores different algorithms that exploit the structure of the quadratic models: the first one applies an \(l_1\)
exact penalty function, the second uses an augmented Lagrangian and the third one combines the former two, resulting in a new algorithm. These methods are implemented within the NOMAD software package and their impact are assessed through computational experiments on 65 analytical test problems and 4 simulation-based engineering applications.
Paru en juin 2016 , 17 pages
Ce cahier a été révisé en novembre 2016