This paper presents a dynamic grouping maintenance strategy for complex systems whose structure may lead to both positive and negative economic dependence which imply that combining maintenance activities is cheaper (or more expensive respectively) than performing maintenance on components separately. Binary Particle Swarm Optimization (BPSO) algorithm is used to find optimal grouping planning which is NP-hard combinatorial problem. The proposed grouping maintenance strategy based on the rolling horizon approach can help to update the maintenance planning by taking into account short-term information which could be changed with time. A numerical example of a 10 components system is finally introduced to illustrate the use and the advantages of the proposed approach in the maintenance optimization framework.