机坪管制移交后机场运行控制中心大厅人员动态排班优化

立足智慧机场的数字化转型要求,针对传统机场运行控制中心（Airport Operational Control Center,AOCC）全时段以最大峰值的静态排班导致工作时长不均、人力资源利用率低、调整灵活性差等问题,以机坪管制移交后的人员分工要求确立动态排班原则,构建AOCC大厅的多目标组合优化的员工排班模型,提出父代班组非支配交叉的基因排序、子代班组拥挤变异算子的遗传算法进行智能搜索最优可行解,并基于Matlab平台进行建模仿真验证,结果表明：手工排班方案作为“父代初始解”确保了飞行安全,交替航班任务实时产生子代班组种群,接班变异保留子代班组精英个体,降低了人力成本、班组人员的工作时长方差和疲劳度

Dynamic Scheduling Optimization of Staff for Airport Operational Control Center After Apron Control Handover

For the traditional Airport Operational Control Center(AOCC) to statically schedule the maximum peak at all times, the working hours are uneven, the utilization of human resources is not high, and the adjustment flexibility is poor. Based on digital transformation requirements of smart airports, the principle for dynamic scheduling was given by the division of labor after transfer of apron control and an optimized employee scheduling model for a multi-objective combination in AOCC hall was established. Non-dominant crossover gene sequencing in the paternal squad and Genetic Algorithm(GA) for crowded variant operators in sub generation squads were proposed to search for the best possible solution and the modeling simulation was verified based on the Matlab platform. The results show that the manual scheduling scheme as the "parent initial solution" ensures flight safety, the alternate flight task generates the sub generation team population in real time, and the succession variation retains the elite individuals of the sub generation team, which reduces the labor cost, the variance of the working hours of the team personnel and the fatigue.