Abstract
A hybrid type of global optimization methods with hierarchical structures is presented. While an intensive search is performed locally on a bounded region given as a neighborhood of a trial local optimum in the lower level, the bounded region is searched diversely to find the best neighborhood in order to prepare a global optimum in the upper level. The diversification and the intensification are known as the search strategies of meta-heuristic methods. The presented method is characterized by the hierarchical combination of the diversification and the intensification, where particle swarm optimization (PSO) accompanied with local search method is used. The effectiveness of PSO is tested in searching the best neighborhood for the global optimum of the benchmarks including a mechanical design problem with integer variables.
