Abstract:

Multiobjective ant colony optimization (ACO) algorithm is used to solve the spacecraft tracking teremetry and command (TT&C) resource scheduling problem (STRSP). Based on the analysis of TT&C characteristics for low earth orbit and medium earth orbit spacecrafts, a multiobjective mathematical formulation for the STRSP is presented, which takes the time window constraints and setup time constraints into account. Then, an improved Pareto-ACO (P-ACO) algorithm referred to the division of labor and cooperation mechanism is put forward to solve the problem. The problem is formulated as path search of task temporal constraint directed graph and the P-ACO algorithm is improved by designing the state transition rules based on the expectation of task choice and the strategy for weights update based on adaptive grid technique. The experimental results demonstrate the proposed algotithm is effective in solving the multiobjective STRSP.