Multi-objective optimisation and decision-making of space station logistics strategies. Issue 13 (2nd October 2016)

• Record Type: Journal Article
• Authors: Zhu, Yue-he; Luo, Ya-zhong
• Is Part Of: International journal of systems science. Volume 47:Issue 13(2016)
• Page Start: 3132
• Page End: 3148
• Publication Date: 2016-10-02
• Subjects: Space station logistics -- multi-objective evolutionary algorithm -- physical programming -- differential evolution algorithm -- decision-making -- preference; System analysis -- Periodicals; 003.3
• DOI: 10.1080/00207721.2015.1091898
• Languages: English
• ISSNs: 0020-7721

Abstract

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.