面向枢纽机场停机位动态分配优化模型及智能调度算法研究

With the rapid development of air transport of China, the contradiction between the rapid growth of the scheduled flights and the limited gates is increasingly sharp in hub airport, how to reasonable assign the limited key resource of gates in order to improve the intelligence level of gates to become an urgent scientific problem to solve. From the view of system engineering, the research methods of the mathematical modeling and in-depth solving are used to explore the dynamic assignment optimization modeling of multi-objective gates and dynamic scheduling problem with the safety and reliability of the running by comprehensive using intelligent optimization algorithms and computer simulation technology. The relation model based on the actual data and simulation between flights and gates is researched to effectively describe the characterization of the solving problem. A new partition optimization model and its solving algorithm based on the combination optimization method are constructed. The dynamical optimization model of multi-objective gate assignment is proposed by combining the classical optimization objectives and robustness optimization objectives. The adaptive swarm intelligence algorithm with multi-strategy is used to solve the dynamical optimization model of multi-objective gates. The optimization model and intelligent rescheduling algorithm of gate reassignment of uncertain flight based on the minimized space disturbance and time disturbance under the dynamic environment are proposed by using the time window concept and multi-conflicting constraints. They provides the rapid intelligent assignment and scheduling of the gates with the theoretical methods. This research takes on the important theoretical significance and practical application value for improving the safe, efficient and reliable operating management of key resources in hub airports.

随着我国民航运输的快速发展，枢纽机场急剧增长的航班量与有限停机位之间矛盾日益尖锐，如何合理分配有限的停机位关键资源，提高停机位分配智能化水平成为一个亟待解决的科学问题。本项目从系统工程角度综合运用智能优化算法和计算机仿真技术，以数学建模与深层次求解为手段，探索兼顾运行安全和可靠的多目标停机位分配建模与智能调度问题。研究基于实际数据与仿真模拟的停机位与航班之间的关联模型，构建基于组合优化的停机位分区优化模型及求解算法；结合经典优化目标和鲁棒性优化目标，建立多目标停机位分配优化模型，利用多策略自适应群智能算法对其求解；基于最小化空间扰动和时间扰动，构建动态环境下不确定航班停机位重分配优化模型及智能重调度算法，为快速实现智能化停机位分配及调度提供理论支撑。本项目的研究对提高我国枢纽机场关键资源的安全高效可靠运行管理具有重要的理论意义和实际应用价值。

停机位作为机场极其稀缺和昂贵的重要资源，是实现航班快速安全停靠，保证航班之间有效衔接，提高整个机场系统容量和服务效率的一个关键因素。本项目从系统工程角度综合运用了智能优化算法和计算机仿真技术，以数学建模与深层次求解为手段，分析了枢纽机场停机位、航班、机位容量等特性影响停机位分配问题的主要因素，研究建立了枢纽机场停机位与航班之间的关联关系模型、枢纽机场停机位分区优化模型、兼顾运行安全和可靠的枢纽机场停机位分配多目标优化模型和面向动态环境下的停机位重分配优化模型；研究提出了基于自适应多变量策略改进的混沌蚁群优化算法、基于多策略改进的蚁群优化算法、基于动态分数阶微分和Alpha稳定分布理论的自适应粒子群优化算法和基于遗传算法和蚁群优化算法的两阶段混合优化算法；进而研究提出了基于改进自适应粒子群优化算法的枢纽机场停机位智能调度方法、基于改进蚁群优化算法的枢纽机场停机位优化分配方法和基于两阶段混合优化算法的枢纽机场延误航班停机位再分配方法；研发了枢纽机场停机位分配系统，为相关研究领域提供了理论与技术支持。. 受本课题资助，经过三年的研究，项目执行情况良好，进展顺利，取得了较好的研究成果。在Applied Soft Computing Journal、Transportation Letters、Soft Computing等国际知名期刊发表学术论文34篇，其中SCI期刊论文17篇，EI期刊论文11篇；授权发明专利1项，申请发明专利1项，软件著作权登记1项，获得辽宁省自然科学学术成果奖二等奖2篇、三等奖2篇；培养硕士生9人，培养博士生2人。