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

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  • Yue-he Zhu
  • Ya-zhong Luo

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.

Suggested Citation

  • Yue-he Zhu & Ya-zhong Luo, 2016. "Multi-objective optimisation and decision-making of space station logistics strategies," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(13), pages 3132-3148, October.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:13:p:3132-3148
    DOI: 10.1080/00207721.2015.1091898
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    Cited by:

    1. Zhijuan Kang & Ming Gao & Wei Dang & Jiajie Wang, 2024. "Optimization Model and Solution Algorithm for Space Station Cargo Supply Planning under Complex Constraints," Sustainability, MDPI, vol. 16(15), pages 1-26, July.

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