优化订单履行过程中的货物装载对提升企业物流系统的工作效率具有十分重要的意义。针对企业在物流场景中遇到的货物尺寸差异大且异构性强的多箱型三维装箱问题,提出了一种货物尺寸分型策略,并以此为基础设计混合启发式算法。在算法中,首先根据货物与托盘的匹配度对货物进行尺寸类型的划分,并分别为不同类型的货物设计相应的装载策略；而后采用最佳拟合算法,为货物筛选出合适的纸箱；最后采用贪婪随机自适应算法求解出订单的装载方案。以某制造业企业的真实订单数据进行实验,验证了本文提出的货物尺寸分型策略和混合启发式算法的有效性,能够为有类似装载问题的企业提供有效的决策支持,提高企业物流装箱的自动化和智能化水平。

To optimize the loading of products in the process of order fulfillment is important to improve the efficiency of the logistics system of enterprises. Aiming at the three-dimensional multiple bin-size bin packing problem with large size differences and strong heterogeneity of products, the size classification strategy was proposed, and a hybrid heuristic algorithm was designed based on it. In the algorithm, firstly, the products were divided into different size types according to the matching degree of products and pallets, and the corresponding loading strategies were designed for different types of them. Then the best fit algorithm was used to select the appropriate cartons for the products. Finally, greedy random adaptive search procedure was used to find the packing plan. Taking the real order as the dataset, the test results show that the proposed algorithm is superior to the traditional three-dimensional packing algorithm, and the layout of the packing plan found by using the size classification strategy is more reasonable, which can provide decision support for similar packing problems.

TP 29

国家自然科学基金项目（面上项目，重点项目，重大项目）