Here some variations of the basic Particle Swarm algorithm (a relatively novel approach for global stochastic optimisation) are proposed in order to increase the efficiency of the search over the solution space with a negligible overhead in the algorithm complexity and speed. The resulting algorithms have been first compared in terms of capability and speed of convergence by their application to a test function, then the resulting best technique has been used for the design of a microwave filter.