基于免疫遗传算法的停机位动态再分配优化  

Gate Dynamic Reassignment Optimization Based on Immune Genetic Algorithm

作　　者：闫萍 刘梦诗 YAN Ping;LIU Meng-shi(School of Economics and Management,Shenyang Aerospace University,Shenyang Liaoning 110136,China)

机构地区：[1]沈阳航空航天大学经济与管理学院,辽宁沈阳110136

出　　处：《计算机仿真》2021年第10期53-57,共5页Computer Simulation

基　　金：教育部人文社会科学研究青年基金项目(18YJC630219);辽宁省教育厅基础研究一般项目(JYT2020023);国家自然科学青年基金项目(71802141,71901153)。

摘　　要：针对兼顾旅客转机行走距离、航班场面滑行距离和停机位使用效率的多目标停机位分配的问题,以最小化航班停机位分配的扰动性为优化目标,建立停机位动态再分配混合整数规划模型。提出基于航班序列的自然数编码方案,设计改进的免疫遗传求解算法,保证个体在遗传操作中的可行性。将免疫算法中个体密度的概念引入对个体适应度值的评价过程,以保持种群的多样性,避免算法过早收敛。实例仿真结果表明,所提出的优化方法能够有效降低延误航班对停机位预分配计划造成的影响。A multi-objective gate assignment problem is studied, which takes into account passenger walking distances, flight taxiing distances, and utilization efficiency of parking space. A mixed-integer programming model of gate dynamic re-assignment is established to minimize the perturbation of flight gate assignment. A natural number coding scheme based on the flight sequence is proposed, and an improved immune genetic algorithm is designed to ensure the feasibility of individuals in genetic operation. The concept of individual density in immune algorithm is introduced into the evaluation process of individual fitness value to keep the diversity of the population and avoid premature convergence of the algorithm. The simulation results show that the proposed optimization method can effectively reduce the impact of delayed flights on the gate pre-assignment plan.

关 键 词：航空运输 停机位分配 混合整数规划 免疫遗传算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]