摘要
为优化研究航空公司所遇到的飞机载重平衡问题,建立了以业载量最大和重心偏移量最小的多目标载重平衡模型,考虑了单舱位限重、多舱位限重、重心限制等约束,运用遗传算法对模型求解,为加快算法寻优能力和加快收敛速度,在普通遗传算法的基础上添加了进化逆转操作算子。最后运用波音757-200F作仿真优化实例,计算结果显示业载量平均可达21281 kg,重心偏移量平均为2.31%MAC,验证了模型的有效性和合理性。
In order to optimize the aircraft load balance problem encountered by airlines,a multi-objective load balance model with the largest business load and the smallest shift in the center of gravity was established,taking into account the limit of single space.Restrictions such as heavy weight,multi-space weight limit,and center of gravity(CG)limit were used to solve the model using an genetic algorithm.In order to speed up the algorithm’s optimization ability and speed up the convergence speed,an evolutionary reversal operation operator was added on the basis of the ordinary genetic algorithm.Finally,using Boeing 757-200 F as a simulation optimization example,the calculation results show that the average load capacity can reach 21281 kg,and the average center of gravity offset is 2.31%MAC,which verifies the validity and rationality of the model.
作者
赵向领
李云飞
李鹏飞
ZHAO Xiang-ling;LI Yun-fei;LI Peng-fei(School of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China;Air Force,Wuhan 430000,China)
出处
《科学技术与工程》
北大核心
2022年第33期14951-14958,共8页
Science Technology and Engineering
基金
国家自然科学基金(71802141)
中央高校基本科研业务费专项资金资助项目(3122018D025)
中国民航大学研究生科研创新资助项目(2021YJS060)。
关键词
航空运输
载重平衡
多目标
遗传算法
进化逆转操作
air transportation
load balance
multi-target
genetic algorithm
evolutionary reversal operation
