基于改进遗传算法的航空集装箱装载优化

Optimization of Aviation Container Loading Based on Improved Genetic Algorithm

目的为保证货物在运输中的平稳性与安全性,优化航空运输中集装箱的装载布局问题,提出一种改进遗传算法并开展航空集装箱装载应用研究。方法考虑货物装载的7种现实约束条件,以集装箱体积利用率为优化目标,建立航空集装箱多箱装载优化模型。采用三段式实数编码随机产生初始种群,并加入最优个体保护策略增强遗传算法的全局收敛性,结合不同约束条件构造合理的适应度函数。结果以真实航空货物信息作为实验数据,实验结果表明在满足多种现实约束的条件下,集装箱体积平均利用率由优化前的74.07%提高到83.99%,装载件数明显增加,适用于航空集装箱的运输装载。结论算法能够应用于航空集装箱装载运输中,为航空运输业实现智能化装载、提高运输效率创造了条件。

In order to ensure the smoothness and safety of cargo in transportation and optimize the problem of con-tainer loading layout in air transportation,an improved genetic algorithm is proposed and the research of air container loading application is carried out.Considering seven practical constraints of cargo loading,taking the container volume utilization rate as the optimization objective,the multi-container loading optimization model of air container is estab-lished.The initial population is randomly generated by three-stage real coding,and the optimal individual protection strategy is added to enhance the global convergence of the genetic algorithm.A reasonable fitness function is con-structed by combining different constraints.Taking the real air cargo information as experimental data,the experimental results show that the average utilization rate of container volume is increased from 74.07%to 83.99%,and the number of loading pieces is significantly increased,which is suitable for air container transportation.The algorithm can be applied to air container loading and transportation,creating conditions for the realization of intelligent loading and the improvement of transportation efficiency in the air transportation industry.