Genetic Algorithm–Based Multiobjective Optimization for 3D Printable Design of a Double-Shell Lunar Habitat Structure

Abstract

The establishment of lunar habitats is significant for humans to explore the Moon and carry out scientific work. Constructing lunar habitats through additive manufacturing using lunar in situ resource is a promising solution. This study proposed a parametric design and multiobjective optimization approach based on genetic algorithms for the structure of lunar habitats. Structural shape was translated into design parameters, which were optimized during the design phase. The optimization objectives were determined considering the material mass consumption, space efficiency, and resistance ability for extreme extraterrestrial environment of the structure. Three kinds of genetic algorithm–based multiobjective optimization methods were used and compared to optimize the structural parameters. The optimized Pareto solution set containing multiple solutions based on the hypervolume index are obtained. Finite-model analysis was performed on the structures of the Pareto solution set and the optimal structure was determined based on the results of maximum stress and displacement. Finally, partially scaled-down physical models were produced through additive manufacturing to demonstrate the optimized double-shell habitat structure.