Multi-objective optimisation and decision-making of space station logistics strategies

ABSTRACT

Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers’ preferences.

KEYWORDS:

• Space station logistics
• multi-objective evolutionary algorithm
• physical programming
• differential evolution algorithm
• decision-making
• preference

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Natural Science Foundation of China [grant number 11222215], the National Program on Key Basic Research Project [grant number 2013CB733100], and the Trans-Century Training Programme Foundation for the Talents by the State Education Commission [grant number NCET-13-0159].

Notes on contributors

Yue-he Zhu

Yue-he Zhu received his BS degree in aircraft manufacturing engineering from Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China, in 2013, and now is studying aerospace engineering for his MS and PhD degrees in the National University of Defense Technology (NUDT), Hunan, China. His current research interests include spacecraft trajectory optimisation and evolutionary computation.

Ya-zhong Luo

Ya-zhong Luo received his BS, MS and PhD degrees in aerospace engineering from NUDT, Hunan, China, in 2001, 2003, and 2007, respectively. Since December 2013, he has been a professor in the College of Aerospace Science and Engineering, NUDT. His current research interests include manned spaceflight mission planning, spacecraft dynamics and control, and evolutionary computation.