An emergent computation approach to the problem of polygon layout with performance constraints

We address the two-dimensional satellite irregular polygons layout problem (TDSIPLP). By mapping the layout problem to a physical system, we present a self-organization emergence algorithm (SEA) based on a multi-agent system (MAS). SEA uses information on the local energy of agents and neighborhood rules to guide interactions between the agents and the environment. System self-organization evolves at a microcosmic level and eventually yields a layout that meets the performance constraints for a satellite. Experiments show that SEA can provide much better performance than other optimization techniques, such as generalized simulated annealing (GSA).