A hybrid discrete particle swarm optimization for satellite scheduling problem

This article analyzes the complex constraints such as time window constraint, capacity limitation, stereo photograph acquisition of satellite scheduling problem in detail, adopts a valued constraint satisfaction problem model, and proposes a new hybrid discrete particle swarm optimization algorithm (HDPSO) for the daily photograph scheduling problem of the SPOT5 satellite. In our algorithm, a local neighborhood topology is used to avoid premature convergence while a branch and bound algorithm is introduced to improve local search capability. In the aspect of constraint handling, a new strategy based on fuzzy repair method along with penalty function is developed. Benchmark problem experimental results show that this algorithm is a feasible and effective approach for solving the daily photograph scheduling problem of the SPOT5 satellite.