  This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS)
algorithm with the Cross-Entropy (CE) method for non smooth constrained
optimization. The CE method is used as a Search step by the MADS algorithm. The
result of this combination retains the convergence properties of MADS and
allows an efficient exploration in order to move away from local minima. The CE
method samples trial points according to a multivariate normal distribution
whose mean and standard deviation are calculated from the best points found so
far. Numerical experiments show an important improvement of this method to
reach the feasible region and to escape local minima.
