Large constellation TT&C resources scheduling method based on improved differential evolution

The scheduling task of TT&C resources is a high complexity dynamic constrained combinatorial optimization problem. Aiming at the issues of large number of satellites, complex types, and high conflict probability of TT&C time windows, this paper proposes an improved adaptive differential evolutionary algorithm to solve the problem of scheduling TT&C resources for large constellation. Firstly, the problem model is constructed, the gain of each TT&C task is a decreasing function over time, and the algorithm needs to maximize the total income; secondly, the adaptive differential evolution algorithm is improved, and a conflict value penalty function algorithm based on the greedy principle is proposed for the conflict cancellation of the time window, which is capable of judging the degree of superiority and inferiority of solution vectors with the same standard. It adopts the sum of the gain minus the sum of the penalty function value as the optimization index to retain the better solution vectors for the optimization process. Thus, the better solution vectors are controlled for iterative evolution. In this paper, three existing algorithms that use different ways to deal with time window conflicts are selected for comparison, and the experimental results show that the algorithm in this paper converges faster, the convergence results are better, and it performs better.