Many-objective optimization and decision-making for overall allocation of space station on-orbit activities

Overall allocation of space station on-orbit activities is the process of allocating a set of on-orbit activities to be executed on the space station in a long-term planning period into several short-term subperiods while balancing logistics demand, resource requirement and the execution priority of on-orbit activities. The basic mathematical model is firstly formulated. Then a heuristic allocation strategy is proposed to reduce optimization difficulty and a hybrid decision-making approach combining physical programming and evolutionary computation is developed to directly search a Pareto-optimal solution, and the performance of these methods in addressing the problem is compared with that of NSGA-III. Three test case with 500, 1000 and 2000 on-orbit activities respectively are simulated to demonstrate the proposed approaches. The results show that the heuristic allocation strategy is effective and performs better than only applying meta-heuristics, and the decision-making approach based on physical programming can efficiently achieve a decision-maker-preferred solution that is converged better than the Pareto frontier obtained by NSGA-III. The obtained allocation scheme satisfies all equilibrium indexes and constraints.