# Multi-Satellite Observation-Relay Transmission-Downloading Coupling Scheduling Method
## 5 Discussion
As compared with the traditional tabu search algorithm, the simulated annealing algorithm and the genetic algorithm reflect the ability and potential of global search, but it takes a longer time to reach the optimal solution. As a consequence of the complexity of the working process and multi-subsystem constraints, it takes more time to calculate the constraint satisfaction of a single solution, which leads to more time consumption in each iteration for each iteration, resulting in an increase in the search time of the entire search method. The search results of the simulated annealing algorithm reflect the uncertainty of the solution caused by the random search process. In order to improve the stability of the results and obtain better outcomes, it is necessary to further reduce the temperature-decreasing rate and increase the number of iterations, which results in an additional rise in calculation time. In the genetic algorithm searching process, due to the multi-subsystem constraints, the generated solutions contain lots of unwanted solutions in a single-step iteration process. It is necessary to adjust the solution to meet the constraints. In this way, it will take more time in the single-step calculation, thus reducing the overall solution efficiency. In the iterative results comparison diagram of the two simulation scenarios, it is apparent that the improved tabu search method and the traditional tabu search method maintain the same search effect at the initial stage of the search. When the traditional tabu search method falls into the local optimum, the improved tabu search method shows the ability to escape from the local optimum. Through the analysis of the observation and data transmission event diagram, it is clear that the reason why the traditional tabu search algorithm falls into the local optimum is due to the coupling constraints of the electricity subsystem and the data transmission subsystem. The improved tabu search algorithm also gives the satellite the ability to observe and transmit more target data by adjusting the state of the satellite cluster subsystems and also to escape the local optimum, which justifies the viewpoint of the improved tabu search method in this article. This research can be further extended in the following aspects:  
1. The global-local combination methods are also an important development direction for search methods. Combining the advantages of global search methods and local search methods, the multi-satellite observation-relay transmission-downloading coupling scheduling method can be improved;
2. Further research can be carried out under different target distributions, ground station distributions, and satellite parameters. Finding out the influence of the parametersof the method on the results under different scenarios. The relationship between the parameters of the algorithm and the adaptive working conditions is explored using system analysis and machine learning in order to enhance the adaptability of the method under different working conditions. In addition, mining the relationship between the parameters of the algorithm and the adaptive scenarios by using system analysis and machine learning methods can enhance the adaptability of the scheduling method in different scenarios. * Study the scheduling method with a large-scale satellite cluster and a large number of targets so as to alleviate the trade-off between calculation results and calculation efficiency in large-scale problems. * In the case of increasing data transmission, how to transmit data to the ground station stably and quickly in the conditions of large data transmission volumes and communication interference is also one of our future research directions.