An Enhanced Multi-Constraint Optimization Algorithm for Efficient Network Topology Generation

In order to address a problem in the research related to the low stability and communication efficiency issues in the generation of optical communication constellation network topology, there is a critical component for sensing the interaction among satellites. This paper makes a novel contribution by proposing a multi-constraint optimization algorithm for optical communication constellation network topology generation. The proposed method significantly improves the existing systems by considering multiple attributes that influence the establishment of inter-satellite links and reducing the impact of subjective factors. This unique approach involves calculating the entropy weight of each attribute using the information entropy method based on the degree of change in each indicator. Subsequently, the weights of the indicators are corrected to obtain the objective weight of each attribute. The comprehensive weight of the link, computed based on the initial link attribute values and weights, serves as the decision basis for link selection, thereby forming the satellite network topology. Upon evaluation, the proposed method has shown remarkable superiority over the compared schemes in terms of communication efficiency and stability.