求解货物在线装箱问题的融合算法

实现集装箱的自动码放规划对于提高装箱容积率、提高经济效益具有重要意义.针对货物在线码放过程中存在的多种实际约束,提出一种由在线极值点(online improved extreme point,IE)算法与模拟退火(simulated annealing,SA)算法结合的在线融合码放(IES)算法,考虑货物尺寸约束,质量约束与装载顺序约束设定多种码放规则以及优化函数,对IE算法中角点坐标序列进行实时迭代更新,并将该角点序列作为初始解序列,基于模拟退火优越的局部搜索能力以及算法的灵活性,两者融合来寻求全局最优角点解坐标.实验结果表明IES算法平均容积率达到89.17％,相比IE算法提高10.34％,证明IES算法在强异构货物实时码放和提高集装箱容积率方面有较好效果.该算法提高了三维装箱算法的工程性,为实现集装箱货物的自动码放创造了必要条件.

Fusion Algorithm for Solving the Problem of Online Cargo Packing

Aiming at the various practical constraints in the process of online cargo stacking, an online fusion stacking algorithm IES was proposed, which combined Online Improved Extreme Point (IE) and simulated annealing algorithm (SA), considering the size of the cargo Constraints, quality constraints and loading sequence constraints seted a variety of stacking rules and optimization functions, real-time iterative update of the corner coordinate sequence in the IE algorithm, and used the corner sequence as the initial solution sequence, based on the superior local search capability of simulated annealing as well as the flexibility of the algorithm, the two merge to find the global optimal corner solution coordinates. Experimental data shows that the average volume rate of the IES algorithm reaches 89.17%, which is 10.34% higher than the IE algorithm, which proves that the proposed method has a good effect in real-time stacking of strong heterogeneous cargo and improving the volume rate of containers. This algorithm can be applied to all industries related to cargo packing, including railways, highways, aviation and shipping, and provides new ideas for practical engineering applications of packing problems in the future.