目的 为解决箱柜类大件货物装箱过程中存在的效率低下、物流成本高的问题，对箱柜类货物的装箱问题展开研究。方法 以功能沙发为例，分析箱柜类货物装箱的常见约束条件，搭建含有体积、重量、摆放方向、装箱顺序的约束的货物码放数学模型，提出一种改进遗传学算法用于数学模型的求解。结果 以45件功能沙发的实际数据进行装箱实验，结果表明算法得出的装载方案合理，在满足箱柜类货物装箱约束的条件下，对货箱的空间利用率达到75%以上。结论 算法对箱柜类大件货物的装箱能够快速得出合理的装箱方案，为复杂情况下货物的装箱提供了一条解决思路。

The work aims to study the packaging of furniture goods to solve such problems as low efficiency and high logistics cost in the packaging process of large furniture goods. With functional sofa as an example, the common packaging constraints of furniture goods were analyzed. A mathematical model for goods stacking with volume, weigh, placement direction and packaging sequence as constraints was built. An improved genetic algorithm was proposed to solve the mathematical model. The actual data of 45 pieces of functional sofa were used for packaging experiments. The results showed that the loading scheme obtained by the proposed algorithm was reasonable. The space utilization rate of the container was more than 75% under the condition of satisfying the packaging constraints of furniture goods. The proposed algorithm can rapidly get a rational packaging solution to the packaging of large furniture goods, which provides a solution to the packaging of goods in complex situations.