摘要
针对机场在突发情况下造成交通流拥挤的问题,引入了CDM理论及算法,并对CDM GDP实施过程及其中的RBS/Compression算法进行研究。研究发现,CDM GDP单纯考虑了进场时隙的分配,未涉及离场容量以及离场时隙的分配问题。因此,基于CDM思想,协同、实时地考虑机场进、离场容量转换问题,在增加机场吞吐率的基础上协同决策进离场序列,给出了进、离场容量优化模型及算法,采用动态规划法进行求解,并结合实际机场航班时刻表数据进行了仿真。结果表明,在特殊外因条件下,进、离场容量相互转换时,协同决策系统能提供最优的解决方案,使机场的进、离场达到最大的吞吐量,并将延误减到最小。
CDM theory is studied aiming at the problems of congested traffic flow at airports under paroxysmal accidents,and by deep study in CDM GDP and RBS/Compression algorithm,we find that CDM GDP only thinks of distribution of arrival slots instead of departure capacity and departure slots.So,based on CDM theory,we study the problems of conversion of arrival ＆ departure capacity collaboratively and in real time.In this paper,we give arrival ＆ departure capacity optimization model and algorithm.We deal with the mode by dynamic programming method.At last,we give simulation to validate the given model.Our experiment results testify that,under the exceptive condition,when arrival capacity can be traded with departure capacity,collaborative decision making optimization system is able to provide the best allocation of capacity to arrivals and departures to maximize the airport throughput and minimize delays.
出处
《系统管理学报》
北大核心
2008年第5期586-590,共5页
Journal of Systems & Management
基金
国家863重点项目资金资助项目(20060112A1033)
