Mutation Particle Swarm Optimization for Earth Observation Satellite Mission Planning

Earth observation satellite mission planning is the core issue of multisatellite and multitask to coordinate control and scheduling problem. In this paper, the 0-1 integer programming model for satellite mission planning problem was constructed. We discussed the discrete particle swarm optimization (DPSO), designed decimal encoding operator of DPSO and decoding method based on the utilization of satellite resources, proposed DPSO with mutation operator (MDPSO). This algorithm not only optimizes effectively, but also has overcome the premature convergence of the particle swarm algorithm. The MDPSO can resolve the satellite mission planning effectively. Finally, we designed two sets of experiments. The first one analyzed the algorithm parameters' influence on the optimization results. Then comparing with the genetic algorithm, we verified the effectiveness of the MDPSO, and confirmed that the optimization results had been significantly improved for at least 7.8%.