Cooperative co-evolutionary algorithm in satellite imaging scheduling of cooperative multiple centers

In this paper, satellite imaging scheduling of cooperative multiple centers, an example of multi-agent systems, is discussed with a proposal of a novel Cooperative CoEvolutionary Planning Algorithm (CCEPA). Considering the numbers of the multi-center and the characteristics of targets to be observed, CCEPA decomposes the tasks into smaller components and evolves multiple solutions in the form of cooperative subpopulations. At the same time, for such evolutionary algorithm based on scheduling, a novel fixed-length binary encoding mechanism for tasks assigned to each center is also proposed. Incorporated with various features like archiving, dynamic sharing, the CCEPA is capable of maintaining archive diversity in the evolution and distributing the solutions uniformly along the Pareto front. Simulation and analysis show that the proposed algorithm can solve the problem effectively.