Multi-objective optimization of space station logistics strategies using physical programming

Abstract

This study extends a previously proposed single-objective optimization formulation of space station logistics strategies to multi-objective optimization. The four-objective model seeks to maximize the mean utilization capacity index, total utilization capacity index, logistics robustness index and flight independency index, aiming to improve both the utilization benefit and the operational robustness of a space station operational scenario. Physical programming is employed to convert the four-objective optimization problem into a single-objective problem. A genetic algorithm is proposed to solve the resulting physical programming-based optimization problem. Moreover, the non-dominated sorting genetic algorithm-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the physical programming-based solution. The proposed approach is demonstrated with a notional one-year scenario of China's future space station. It is shown that the designer-preferred compromise solution improving both the utilization benefit and the operational robustness is successfully obtained.

Keywords:

• space station
• logistics strategy
• multi-objective optimization
• physical programming

Additional information

Funding

This work was partially supported by the National Natural Science Foundation of China [no. 11272346], Foundation for the Author of National Excellent Doctoral Dissertation of PR China [no. 201171] and the Program for New Century Excellent Talents in University [no. NCET-13-0159].