基于改进NSGA2的航空运输优化

为了降低航空运输过程中产生的燃油成本,同时最大程度地满足指挥人员提出的保障需求,根据运输飞机在行动中需要运输的人员物资数量及目的地位置,建立追求航次最小飞行成本并考虑时间约束的飞行速度优化模型,运用改进的带精英策略的非支配排序遗传算法(NSGA2)对飞行速度进行优化选择。设计算例实验,比较其与传统NSGA2算法在计算性能上的区别,用以验证结合了修饰算子与改进的初始解生成策略的算法的有效性。结果表明,改进算法的求解精度和准度均能达到要求,且在相同精度上改进的NSGA2算法能够节省25.38%的时间,显著改变飞行速度优化的结果,提高了航空运输的效率。

Optimization of air transport based on improved NSGA2

To reduce fuel costs generated in the process of transport aviation, and meet the security needs of the commanding officers, according to the number of personnel and goods that the transport aircraft in operations need to transport and its destination, the aircraft speed optimization model was established which pursues minimum flight cost and considers time constraints, and flight speed optimized by improved nondominated sorting genetic algorithm 2(NSGA2).By conducting numerical tests, the distinguishing performance of improved NSGA2 was compared with classical NSGA2 without modification to verify the effectiveness of the algorithm combined with modifying operators and the improved strategy of initial solution generation. The results show that the precision and accuracy of the improved algorithm can meet the requirements, and save time by 25-38% with the same degree of accuracy. The use of the algorithm for optimizing aircraft speed selection dramatically changes the flight speed optimization results and improves the efficiency of air transport.