Satellites scheduling based on DMC encoded method and Pareto Front Motivated Particle Swarm Optimization algorithm

This paper focuses on solving satellites scheduling problem in the case of multi-targets and multi-objective optimization. First, Dynamic Matrix Cluster (DMC) encoding method is proposed, which resolves resource conflicts during coding stage to avoid repeated attempts and judgments during evolvement stage, resulting in higher time efficiency of the algorithm; Second, Pareto Front Motivated Particle Swarm Optimization (PF-PSO) is proposed, which uses Pareto Front to keep a set of optimal solutions, avoiding getting stuck in local optimization, also leading to more optimal solutions diverse in different index optimization priority. Finally, stimulation results indicate that PF-PSO encoded by DMC consumes less time to finish evolvement process and reach a better fitness than traditional PSO method.