Abstract: An adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm is introduced to solve the problem of Lambert dual pulse orbital interception, which aims to achieve the minimum fuel consumption by optimizing the sum of the speed increments of the two pulses. First, a mathematical model of orbit change interception is constructed based on Lambert's fixed time flight theorem. Assuming that the spacecraft maneuvers to pursue the target within one week of its initial orbit flight, the time of two pulse orbit changes is set as the decision variable, the fuel consumption is taken as the fitness function, and the ASAPSO hybrid algorithm is adopted as the optimization strategy. Secondly, in order to verify the effectiveness of ASAPSO algorithm, traditional particle swarm optimization (PSO)，simulated annealing particle swarm optimization (SAPSO) and reinforcement learning particle swarm optimization (RLPSO) are used to optimize the same model. The comparison shows that ASAPSO algorithm can quickly converge to the global optimal solution in less iterations, which greatly reduces the computation amount and time to deal with the orbital interception problem. The algorithm combines the global search capability of PSO and the local optimization characteristics of SA to provide a more efficient and accurate solution to the Lambert double pulse orbit change interception problem.

Key words: Lambert orbit interception, particle swarm optimization algorithm, simulated annealing algorithm, parameter adaptive