Selection strategies for initial positions and initial velocities in multi-optima particle swarms

Standard particle swarm optimization cannot guarantee convergence to the global optimum in multi-modal search spaces, so multiple swarms can be useful. The multiple swarms all need initial positions and initial velocities for their particles. Several simple strategies to select initial positions and initial velocities are presented. A series of experiments isolates the effects of these selected initial positions and velocities compared to random initial positions and velocities. A first set of experiments shows how locust swarms benefit from 'scouting' for initial positions and the use of initial velocities that 'launch away' from the previous optimum. A second set of experiments show that the performance of WoSP (Waves of Swarm Particles) can be improved by using new search strategies to select the initial positions and initial velocities for the particles in its sub-swarms.