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为解决传统遗传算法(GA)在某轻型飞机第Ⅱ类U型装配线平衡问题(UALBP-Ⅱ)优化计算中容易陷入早熟的问题,应用Memetic算法进行平衡优化计算。考虑了设备能力,以装配线节拍的最小化和各工作站间能力平衡为优化目标,针对某轻型飞机的U型装配线,建立了多目标、多类约束数学模型,并给出工序操作顺序、设备能力等约束条件。在标准遗传算法基础上引入贪婪算法,实现全局和局部寻优,并给出算法的流程。最后以某轻型飞机装配线为对象进行优化计算,通过对Memetic算法和标准遗传算法求解结果的比较,说明Memetic算法收敛性更好,能更快地找到目标函数的最优解。
In order to solve the problem that traditional genetic algorithm (GA) is apt to fall premature in the optimization calculation of UALB II of a light aircraft, Memetic algorithm is used to balance and optimize the calculation. Considering the equipment capability, taking the minimization of the assembly line beat and the capability balance among the work stations as optimization objectives, a multi-objective and multi-class constrained mathematic model is established for the U-shaped assembly line of a light aircraft. The order of operation and equipment capability Other constraints. Based on the standard genetic algorithm, a greedy algorithm is introduced to achieve global and local optimization, and the algorithm flow is given. Finally, a light aircraft assembly line is optimized for the calculation. The comparison between the Memetic algorithm and the standard genetic algorithm shows that the Memetic algorithm has better convergence and can find the optimal solution of the objective function more quickly.