Comparison of NEWUOA with different numbers of interpolation points on the BBOB noisy testbed

In this paper, we study the performances of the NEW Unconstrained Optimization Algorithm (NEWUOA) with different numbers of interpolation points. NEWUOA is a trust region method, the number of points used to build the surrogate model is an input parameter of the algorithm. We compare the performances of NEWUOA using three different number of points in search spaces of dimension from two to forty on problems from the BBOB 2009 noisy function testbed. Using the maximum number of interpolation points grants the better results in this noisy setting.