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集装箱装载问题以假设货物为规则实体进行研究,方便了相关求解算法的改进,但是忽略货物本身空腔的存在,已经开始阻碍集装箱装载率的进一步提高。对于现有文献很少研究的货物空腔背景下的集装箱装载问题,设计一种基于遗传算法的空间优化模型。模型通过空间预处理,将货物按照一定规则嵌套填充,使不可用或小型货物空腔叠加成较大的可用空间;定义一种四叉树空间结构来表达空间的分解;提出并运用四空间分割法来设计装载策略;引入自适应遗传算法,进行模型寻优。最后案例分析表明,该模型可以大大减弱空腔对整体装载率的降低作用,在实际应用时具有一定的参考价值。
The problem of container loading is based on the assumption that the goods are regular entities, which facilitates the improvement of the relevant solving algorithms. However, neglecting the existence of cavities in the cargo itself has begun to hinder the further improvement of container loading rate. For the problem of container loading under the background of cargo space, which is seldom studied in the existing literature, a space optimization model based on genetic algorithm is designed. The model pretreats the goods by nested and filled the goods according to certain rules so that the available or small cargo cavities are superposed into larger available space. A quadtree space structure is defined to express the space decomposition. The four space Segmentation method to design loading strategy; introduce adaptive genetic algorithm to optimize the model. The final case analysis shows that the model can greatly reduce the cavity to reduce the overall loading rate, which has some reference value in practical application.