基于改进遗传算法的航空器载重平衡

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21 281kg,重心偏移量平均为2.31%MAC，验证了模型的有效性和合理性。

Research on Aircraft Load Balance Based on Improved Genetic Algorithm

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 757-200F as a simulation optimization example, the calculation results show that the average load capacity can reach 21 281 kg, and the average center of gravity offset is 2. 31% MAC, which verifies the validity and rationality of the model.