目的 针对以空间利用率最大为目标的三维装箱问题，设计基于优先保持策略的改进遗传算法，并对其进行求解。方法 首先，在分析现有相关研究存在不足的基础上，提出优先保持策略的基本改进理念;其次，针对问题特点，设计改进遗传算法的基本流程，重点对交叉和变异的详细实现进行介绍;最后，通过实验仿真的方式，对求解结果和算法性能进行对比分析。结果 实验证明，在所用算例中，算法的求解结果优于对比算法约14%，且收敛更为稳定，时耗满足一般需求。结论 文中算法具有较优异的迭代性能。

Aiming at the three-dimensional container loading problem with maximum space utilization as the goal, this research proposes an improved genetic algorithm based on the priority retention strategy to solve it. First, based on the analysis of existing related research deficiencies, the basic improvement concept of the priority retention strategy is proposed. Second, the basic process of improving the genetic algorithm is designed according to the characteristics of the problem, focusing on the detailed implementation of crossover and mutation. Finally, through experimental simulation, the solution results and algorithm performance are compared and analyzed. Experiments have proved that the algorithm has better solution results (about 14% better than the compared algorithm), the convergence is more stable, and energy consumption meet general needs. Therefore, this algorithm has relatively excellent iterative performance.