Solving unconstrained optimization problem with a filter-based nonmonotone pattern search algorithm

This paper proposes a new frame-based pattern search algorithm for unconstrained optimization. The implementation of filter leads the sequence of function values at iterates {x(k)}{x(k)} nonmonotonically decreasing and thus motivates us to consider nonmonotone technique. Furthermore, the use of these two techniques can improve the efficiency of general pattern search algorithms. The numerical results show that the new algorithm is practical and efficient.