Selection of variables in parallel space decomposition for the mesh adaptive direct search algorithm

The parallel space decomposition of the Mesh Adaptive Direct Search algorithm (PSDMADS proposed in 2008) is an asynchronous parallel method for constrained derivative-free optimization with large number of variables. It uses a simple generic strategy to decompose a problem into smaller dimension subproblems. The present work explores new strategies for selecting subset of variables defining … Read more

Efficient solution of quadratically constrained quadratic subproblems within the MADS algorithm

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: … Read more