面向航班延误场景的机位预分配模型及算法研究-学报杂志社

期刊信息

合肥工业大学（自然科学版），2023年8月，第46卷第8期：1079-1085

DOI: 10.3969/j.issn.1003-5060.2023.08.011

作者信息

王鑫晨 $ ^{1} $，吕增威 $ ^{1,2} $，魏振春 $ ^{1,2} $，张浩 $ ^{3} $

(1. 合肥工业大学计算机与信息学院, 安徽合肥 230601; 2. 安全关键工业测控技术教育部工程研究中心, 安徽合肥 230601; 3. 飞友科技有限公司, 安徽合肥 230031)

摘要和关键词

摘要: 针对航班延误场景下易出现机位变更的问题,文章以最小化机位冲突概率和最大化乘客靠桥率为目标,增加基于机位冲突概率的鲁棒性约束,结合机场实际业务规则构建具有良好抗延误特性的机位预分配模型,并将其建模为马尔可夫决策模型,提出基于异步优势动作评价的机位预分配算法(gate assignment algorithm based on asynchronous advantage actor-critic, GABA3C)求解该问题。为验证所提算法在各种变化场景下的适用性,文章设置3组场景实例。仿真结果表明,所提出的算法在有效提升旅客满意度的同时,还可以解决因航班延误造成的机位冲突问题。相比于自适应并行遗传算法(adaptive parallel genetic algorithm, APGA)、近端策略优化(proximal policy optimization, PPO)算法以及深度Q网络(deep Q-network, DQN)算法,该文所提算法求得的解在乘客靠桥率上的目标值分别提高了5.7%、4.6%、5.8%,在机位冲突概率上的目标值分别降低了23.5%、10.0%、17.4%。

关键词: 航班延误；机位预分配；异步优势动作评价；机位冲突概率；旅客满意度

Authors

WANG Xinchen $ ^{1} $, LYU Zengwei $ ^{1,2} $, WEI Zhenchun $ ^{1,2} $, ZHANG Hao $ ^{3} $

(1. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China; 2. Engineering Research Center of Safety Critical Industrial Measurement and Control Technology of Ministry of Education, Hefei 230601, China; 3. Feeyo Technology Co., Ltd., Hefei 230031, China)

Abstract and Keywords

Abstract: In order to solve the problem of gate change in the flight delay scenario, this paper aims to minimize the probability of gate conflict and maximize the near-gate passenger allocation rate, increases the robustness constraints based on the gate conflict probability, and constructs a gate pre-assignment model with good anti-delay characteristics combined with the actual airport business rules. It is modeled as a Markov decision model, and a gate assignment algorithm based on asynchronous advantage actor-critic(GABA3C) is proposed to solve this problem. In order to verify the applicability of the proposed algorithm in various changing scenarios, three sets of scenario examples are set up. Simulation results show that the proposed algorithm can effectively improve passenger satisfaction and solve the problem of gate conflict caused by flight delays. Compared with adaptive parallel genetic algorithm(APGA), proximal policy optimization(PPO) and deep Q-network(DQN) algorithm, the target value of solutions obtained by the proposed algorithm in the near-gate passenger allocation rate is increased by 5.7%, 4.6% and 5.8%, respectively, and the target value in the gate conflict probability is reduced by 23.5%, 10.0% and 17.4%, respectively.

Keywords: flight delay; gate pre-assignment; asynchronous advantage actor-critic(A3C); gate conflict

基金信息

国家自然科学基金资助项目（62002097）；安徽省重点研究与开发计划资助项目（201904a07020030）和中央高校基本科研业务费专项资金资助项目（PA2021GDGP0061）

合肥工业大学学报(自然科学版)

导航菜单

面向航班延误场景的机位预分配模型及算法研究