Dynamic Gate Assignment Method for Improving Flight Bridge Rate
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摘要:
航班靠桥率是衡量航空服务质量和机场运行效率的一项重要指标. 为提高航班靠桥率，提出一种基于现有业务流程、考虑拖曳条件的机位动态分配优化方法. 通过分阶段安排全日机位分配计划，全面考虑拖曳航班的停放时间限制、拖曳判定条件及拖曳机位类型约束，构建以提升航班靠桥率为核心目标的机位分配模型；该模型以拖曳惩罚成本为依据，对分配至近机位的航班数量进行优化，以实现整体效益最大化；同时，针对传统机位预分配难以适应航班动态运行变化的问题，设计基于改进遗传算法的多阶段动态分配算法，通过继续分配机制锁定已完成分配结果，并持续优化新增航班机位分配；最后，运用西南某大型繁忙机场的实际运行数据开展仿真实验，对所提模型与方法的有效性进行验证. 结果表明：相较于不考虑拖曳的传统机位分配模型，考虑拖曳策略的模型使航班靠桥率提高了1.1%；在此基础上，相较于传统遗传算法，采用多阶段动态分配方法使航班靠桥率提升了4.0%，航班拖曳频次降低了16.6%，该方法能够有效权衡近机位分配与航空器拖曳成本，在保证拖曳成本可控的前提下进一步优化靠桥率，为机场航班靠桥率提升及机位动态分配提供了一种可行的优化方法.
Abstract:Flight bridge rate is a key indicator for evaluating aviation service quality and airport operational efficiency. To improve the flight bridge rate, an optimized dynamic gate assignment method based on existing operational workflows and towing conditions was proposed. By arranging the full-day gate assignment plan in stages, and comprehensively considering constraints such as parking time limits for towed flights, towing eligibility conditions, and towing gate type restrictions, a gate assignment model taking the improvement of the flight bridge rate as the core objective was constructed. The number of flights assigned to contact gates was optimized by the model based on the towing penalty cost to maximize the overall efficiency. Meanwhile, to address the problem that the traditional pre-flight gate assignment is difficult to adapt to dynamic changes in flight operations, a multi-stage dynamic assignment algorithm based on an improved genetic algorithm was designed. In this algorithm, a continuous assignment mechanism was adopted to lock the completed assignment results, and the gate assignment for newly added flights was continuously optimized. Finally, simulation experiments were carried out using the actual operational data of a busy large-scale airport in Southwest China to verify the effectiveness of the proposed model and method. The results show that compared with the traditional gate assignment model without considering towing, the model considering the towing strategy increases the flight bridge rate by 1.1%; on this basis, compared with the traditional genetic algorithm, the adopted multi-stage dynamic assignment method increases the flight bridge rate by 4.0% and decreases the flight towing frequency by 16.6%. The proposed method can effectively balance the assignment of contact gates and aircraft towing costs, further optimize the flight bridge rate on the premise of controllable towing costs, and provide a feasible optimization method for the improvement of the flight bridge rate and dynamic gate assignment at airports.
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Key words:
- air transportation /
- flight bridge rate /
- dynamic gate assignment /
- genetic algorithm /
- aircraft towing
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图 5 多阶段分配适应度值变化曲线
Figure 5. Variation curves of fitness value in multi-stage assignment
图 6 3个阶段累积近机位航班数和拖曳次数
Figure 6. Cumulative number of contact gate flights and tows in three stages
表 1 航班数据（部分）
Table 1. Partial flight data
航班号 航班编号 航司 机型 翼展/m 机身长度/m 计划到港时间 计划离港时间 OQ235V 1 OQ A319 34.10 33.84 0755 1200 9H8333 2 9H A320 34.10 37.57 0805 0910 SC2310 3 SC A321 34.10 44.51 0810 0925 9C8613 4 9C B737-800 34.40 39.50 0835 0940 3U8283 5 3U B787-9 60.12 62.81 0840 0955 $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ 
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表 2 停机位数据（部分）
Table 2. Partial aircraft stand data
停机位 机位编号 限制翼展/m 限制机身长度/m 可用航司 是否是近机位 201 ～ 205 1 ～ 5 < 36.00 3U等 1 206 6 < 47.60 3U等 1 $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ 314～316 42～44 ≤ 48.00 ≤ 55.00 CA,CZ,ZH,SC,MU,FM等 1 $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ 714 125 ≤ 68.50 ≤ 76.40 CA,HU,FM,CZ,MU等 0
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表 3 机位分配拖曳结果
Table 3. Towing results of gate assignment
阶段 拖曳航班
编号进港航班
分配机位离港航班
分配机位$ {t}_{\text{g,}i}-{t}_{\text{STA},i} $/min 阶段1 6 15（近） 99（远） 782 49 98（远） 41（近） 127 73 106（远） 30（近） 121 阶段2 100 1（近） 110（远） 129 124 94（远） 1（近） 126 143 95（远） 36（近） 181 151 4（近） 97（远） 150 152 96（远） 17（近） 216 155 12（近） 115（远） 143 164 39（近） 111（远） 127 183 92（远） 52（近） 231 203 18（近） 93（远） 212 阶段3 248 47（近） 101（远） 188 262 97（远） 18（近） 143 280 114（远） 80（近） 121
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