Solving 3D Container Loading Problems Using Physics Simulation for Genetic Algorithm Evaluation
Solving 3D Container Loading Problems Using Physics Simulation for Genetic Algorithm Evaluation
复制标题
DOI：
10.1587/transinf.2020edp7239
复制
发表时间：
2021-11
期刊：
影响因子：
--
通讯作者：
Shuhei Nishiyama;Chonho Lee;T. Mashita
中科院分区：
文献类型：
--
作者：
Shuhei Nishiyama;Chonho Lee;T. Mashita
总结在这项工作中，提出了一种多约束的三维集装箱装载问题的优化方法。该方法由遗传算法组成，以生成货物的安排和使用物理模拟的适合性评估。该函数不仅考虑了集装箱密度和适应值的最大化，而且考虑了几个不同的约束条件，如重量，可堆叠性，易碎性和货物的方向。我们采用集装箱摇晃模拟进行适合性评估，以包括装载和运输期间的约束因素。我们验证了艾德，所提出的方法成功地提供了最佳的货物安排的小规模问题，约10件货物
SUMMARY In this work, an optimization method for the 3D container loading problem with multiple constraints is proposed. The method consists of a genetic algorithm to generate an arrangement of cargo and a fit-ness evaluation using a physics simulation. The fitness function considers not only the maximization of the container density and fitness value but also several di ff erent constraints such as weight, stack-ability, fragility, and orientation of cargo pieces. We employed a container shaking simulation for the fitness evaluation to include constraint e ff ects during loading and transportation. We verified that the proposed method successfully provides the optimal cargo arrangement for small-scale problems with about 10 pieces of cargo