Joint optimization of green low-carbon oriented flight launch strategy and towing operation plan
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摘要:
为减少离港航空器在推出滑行过程中产生的碳排放，提出一类基于绿色低碳导向的航空器牵引推出作业调度优化模型。根据航空器场面滑行状态及延误情况，在考虑航空器机坪运行规则的基础上，建立航班推出时刻动态调整机制，定义柔性推出缓冲时间，量化动态牵引推出条件，建立考虑碳排放的航空器牵引调度混合整数规划模型，结合牵引推出机-车协同调度优化计划降低场面滑行碳排放水平。考虑到整数规划模型为复杂非线性结构，求解难度较大，提出基于线性迭代的两阶段算法求解。采用天津滨海国际机场数据开展案例分析，标定调度优化模型中关键参数并验证该模型的可行性。结果表明：与现情况相比，通过对牵引推出计划的优化，航空器场面运行排放降低7.98%。研究结果对机场飞行区低碳运行及机-车协同调度提供决策支持。
Abstract:To reduce carbon emissions during the departure taxiing process of outbound aircraft, this paper proposes a type of optimization model for aircraft towing operations based on a green and low-carbon approach. The flexible launch buffer time is defined, the dynamic traction launch conditions are quantified, the aircraft traction scheduling mixed integer programming model taking carbon emissions into account, and the dynamic adjustment mechanism of flight launch time is established based on the operation rules of the aircraft apron based on the taxiing state and delay of the aircraft surface. The carbon emission level of surface taxiing is reduced by combining the optimization of the traction roll-out motor-vehicle collaborative scheduling plan. The model integrates the optimization of aircraft-towing dispatch plans to reduce carbon emissions during apron taxiing. Considering the complexity and non-linearity of the model, a two-stage algorithm based on linear iteration is proposed for solving. Tianjin Binhai International Airport data is used for case studies, and the model's viability is confirmed and important model parameters are calibrated. The results of the case study indicate that, compared to the current situation, optimizing the towing departure plan reduces emissions during apron operations by 7.98%. The research findings provide decision support for achieving low-carbon operations in the airport apron area and optimizing aircraft-towing dispatch plans.
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Key words:
- air transportation /
- airport /
- towing /
- linearization algorithm /
- green and low-carbon
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图 1 航空器牵引调度优化模型流程示意图
Figure 1. Schematic diagram of aircraft towing scheduling optimization model process
表 1 航班基础数据
Table 1. Basic flight data
航空器
序号停机位
序号最早开始
服务时刻计划推出
时刻柔性推出缓冲
时刻上限1 1 9:06 9:11 9:16 2 2 9:20 9:25 9:30 3 3 9:00 9:05 9:10 4 4 9:08 9:16 9:18 5 5 9:33 9:38 9:43 6 6 10:07 10:12 10:17 7 7 10:20 10:25 10:30 8 8 9:04 9:09 9:14 9 9 9:35 9:40 9:45 10 10 9:23 9:28 9:33 11 11 9:53 9:58 10:03 12 12 9:02 9:07 9:12 13 13 10:17 10:22 10:27 14 14 10:04 10:09 10:14 15 15 10:59 11:04 11:09 16 16 9:26 9:31 9:36 17 17 9:10 9:15 9:20 18 18 9:14 9:19 9:24 19 19 9:17 9:22 9:27 20 20 9:25 9:30 9:35 21 21 9:28 9:33 9:38 22 22 9:54 9:59 10:04 23 23 9:38 9:43 9:48 24 24 9:57 10:02 10:07 25 25 9:40 9:45 9:50 26 26 10:01 10:06 10:11 27 27 10:10 10:16 10:20 28 28 10:14 10:19 10:24 29 29 10:33 10:38 10:43 30 30 10:23 10:28 10:33 31 31 10:40 10:45 10:50 32 32 10:57 11:02 11:07 33 33 10:46 10:51 10:56 34 34 10:48 10:53 10:58 35 35 10:53 10:58 11:03 
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表 2 案例参数
Table 2. Case parameters
单车固定
启用成本/元车辆运行
成本/（元·min−1）燃油碳排放
系数/（kg·kg−1）碳排放量的
排放成本/（元·kg−1）最小安全起飞
间隔/min最晚推出
时刻/min航空器单位运行
成本/（元·min−1）航空燃油
价格/（元·kg−1）1000 1 3.115 0.28 3 20 133.76 4.5
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表 3 优化后航空器牵引调度方案
Table 3. Aircraft traction scheduling scheme
牵引车辆编号 牵引航空器序号 1 18→24→14(0.18)→34 2 17→2→20(0.9)→31→7(0.9) 3 16→6→30→26(4.2) 4 8→25→22→13 5 12→10→11→3(5.82)→15(2.58) 6 4→29 7 19→9→21(0.84)→27→35 8 5→23→28→1(5.22)→32(0.96)→33(3.3)
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表 4 优化结果
Table 4. Optimization results
牵引调度模型 牵引作业
总时间/min航空器滑行碳
排放量/ kg目标函数值/元 现状 392.61 27427.58 88568.16 本文调度优化模型 367.24 25238.70 81820.80 最大柔性推出时间方案 389.44 26415.20 83239.80
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表 5 不同车辆数的优化结果
Table 5. Optimization results for different numbers of vehicles
车辆数目 航空器滑行碳排放量/kg 车辆运行成本/元 航空器运行成本/元 5 27770.22 5259.97 42827.50 6 25898.56 6263.62 41730.00 7 25840.19 7266.59 41535.00 8 25238.70 8268.32 37147.50 9 23529.20 9273.36 36660.00 10 25723.45 10274.32 37160.68 11 25752.63 11283.87 37202.84 12 25956.93 12291.36 37497.97
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表 6 不同航空器数目的优化结果
Table 6. Optimization results for different numbers of aircrafts
航空器
数目优化前航空器滑行
碳排放量/kg优化后航空器滑行
碳排放量/kg碳排放量优化
百分比/%优化前目标
函数值/元优化后目标
函数值/元目标函数值优化
百分比/%20 15658.06 15050.64 3.88 49074.00 47319.00 3.58 25 19842.55 18627.70 6.12 62005.20 58495.20 5.66 30 24263.25 22339.74 7.93 74974.25 70426.20 6.07 35 27427.58 25238.70 7.98 88568.16 81820.80 7.62 40 33727.66 28665.79 15.01 111834.90 97989.90 12.38
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表 7 高峰期航空器优化结果
Table 7. Peak time optimization results for aircraft
牵引调度
模型牵引作业
总时间/min航空器滑行
碳排放量/kg目标
函数值/元现状 539.81 43415.31 145257.45 本文调度优化模型 483.17 36749.21 124575.90
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表 8 算法对比结果
Table 8. Comparison of algorithms
算法类型 求解时间/ min 目标函数值/元 遗传算法 6 82 347.20 线性迭代算法 3 81 820.80
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