G-2016-45
Efficient solution of quadratically constrained quadratic subproblems within a direct-search algorithm
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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