目的 针对同构散货集装箱装载中包装箱尺寸固定、空间适配性差、装载重量与空间利用率难以协同提升的问题,构建包装箱尺寸与装载方案的联合优化模型,实现散货集装箱运输效益的提升。方法 以包装箱尺寸动态优化为核心,提出双层网格启发式算法（DLGSH）,将三维装箱问题通过空间四分策略简化为二维布局问题,以毫米为步长全局搜索最优包装箱尺寸并协同优化二维布局方案。在容重、尺寸比例、包装厚度等约束下实现尺寸优化与装载布局的协同求解并从理论与仿真两方面验证算法有效性。结果 基于某大米加工企业4种产品规格的实验表明,装载重量提升14.67%至31.72%、空间利用率提升1.62%至12.79%。基于10组差异化算例,DLGSH相较混合遗传算法、三阶段计算智能框架的装载重量平均优势分别为2.16%、2.40%。结论 DLGSH求解稳定、全局搜索能力强,可为散货集装箱装载优化与物流包装设计提供支持。
Abstract
To address the issues of fixed packaging box dimensions, poor space adaptability and the difficulty of jointly improving loading weight and space utilization in homogeneous bulk cargo container loading, the work aims to construct a joint optimization model for packaging box dimensions and loading schemes to enhance the transport benefits of bulk cargo containers. Centered on dynamic packaging box dimension optimization, a Dual-Layer Grid Search Heuristic (DLGSH) was proposed. The three-dimensional bin packing problem was reduced to a two-dimensional layout problem via a spatial quartering strategy, and optimal packaging box dimensions were globally searched at a millimeter step size while the two-dimensional layout was jointly optimized. Under constraints such as bulk density, dimension ratios, and packaging thickness, the collaborative solution of dimensional optimization and loading layout was achieved and the effectiveness of the algorithm was verified from both theoretical and simulation aspects. Experiments based on four product specifications at a rice-processing enterprise showed that loading weight increased by 14.67%-31.72% and space utilization by 1.62-12.79%. Across 10 differentiated test cases, DLGSH achieved average loading-weight advantages of 2.16% and 2.40% over a hybrid genetic algorithm and a three-stage computational intelligence framework, respectively. DLGSH demonstrates stable solution quality and strong global search capability, providing support for bulk cargo container loading optimization and logistics packaging design.
关键词
集装箱装载优化 /
物品尺寸可变 /
双层网格启发式算法 /
空间四分策略
Key words
container loading optimization /
variable dimension items /
dual-layer grid search heuristic algorithm /
spatial quartering strategy
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基金
北京市教委科技规划一般项目（SM202410037007）
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