Joint Optimisation of the Gate and Taxi Route During Peak Hours: A Fusion Algorithm of Adaptive Genetic and Artificial Bee Colony

IF 2.7 4区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IET Intelligent Transport Systems Pub Date : 2026-01-31 DOI:10.1049/itr2.70162

Fujun Wang, Dongqing Liu, Xiangyi Li, Wei Zhang, Hongfei Liu, Jun Bi

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引用次数: 0

Abstract

The joint optimisation of parking gates and taxiing time is critical in improving airport operation efficiency. However, there is a lack of effective solutions to this problem, especially during peak hours. This paper constructs a joint optimisation model for parking gate and taxiing route assignment based on column generation (CG). An artificial bee colony–adaptive genetic algorithm fusion is designed to solve the joint model considering CG characteristics and can operate in parallel. Then this paper uses the actual data from Beijing Capital International Airport (PEK) and Kunming Changshui International Airport (KMG) to verify the proposed method. It is proved that this study can effectively improve parking gate and taxiway utilisation compared with the actual allocation results and baseline algorithms. Meanwhile, in peak hours, this method can still give stable results at an acceptable time.

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高峰时段登机口与出租车路线联合优化：一种自适应遗传与人工蜂群融合算法

停车闸口与滑行时间的联合优化是提高机场运行效率的关键。然而，这一问题缺乏有效的解决方案，尤其是在高峰时段。本文建立了一个基于列生成（CG）的停车门与滑行路线分配联合优化模型。考虑CG特性，设计了一种人工蜂群自适应融合遗传算法求解联合模型，并可并行运行。然后利用北京首都国际机场（PEK）和昆明长水国际机场（KMG）的实际数据对本文提出的方法进行了验证。与实际分配结果和基线算法进行比较，证明本研究能有效提高泊车闸口和滑行道的利用率。同时，在高峰时段，该方法仍能在可接受的时间内给出稳定的结果。

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来源期刊

IET Intelligent Transport Systems 工程技术-运输科技

CiteScore

6.50

自引率

7.40%

发文量

159

审稿时长

3 months

期刊介绍： IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf