Multi-swarm systems base their search on multiple sub-swarms instead of one standard swarm. The use of diverse sub-swarms increases performance when optimizing multi-modal functions. However, new design decisions arise when implementing multi-swarm systems such as how to select the initial positions and initial velocities, and how to coordinate the different sub-swarms. Starting from the relatively simple multi-swarm system of locust swarms, ideas from differential evolution and estimation of distribution algorithms are used to address the new design considerations that are specific to multi-swarm systems. Experiments show that the new hybrid system can perform better than each of the individual components.