考虑带时间窗的多机型航班加油车三阶段调度优化

邢志伟; 周芳宇; 孙恪; 李雅婷

doi:10.13700/j.bh.1001-5965.2024.0332

考虑带时间窗的多机型航班加油车三阶段调度优化

doi: 10.13700/j.bh.1001-5965.2024.0332

中国民航大学电子信息与自动化学院，天津 300300

基金项目:

国家自然科学基金(U2333205)；中国民航大学研究生科研创新项目(2023YJSKC02012)

详细信息

通讯作者:
E-mail：cauc_xzw@163.com

中图分类号: U268.6
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出版历程
- 收稿日期: 2024-05-17
- 录用日期: 2024-09-06
- 网络出版日期: 2024-09-24
- 整期出版日期: 2026-07-31

Considering three-stage scheduling optimization of multi-type flight refueling vehicles with time windows

School of Electronic Information and Automation，Civil Aviation University of China，Tianjin 300300，China

Funds:

National Natural Science Foundation of China (U2333205); Civil Aviation University of China Research Innovation Project for Postgraduate Students (2023YJSKC02012)

More Information

Corresponding author: E-mail: cauc_xzw@163.com

摘要

摘要:
为解决机场航班保障过程中加油车调度效率低下的问题，在航班安全作业的前提下确定航班的加油时间窗和可开始加油时间窗双约束条件，并对机坪位置与机位编号进行标准化处理，研究3种应用场景下的核心变量，构建3种双约束条件下的以加油车数量为优化目标的整数规划模型。针对不同的模型，根据机场实际运行情况提出引入精英策略的遗传优化算法对模型进行求解。在第①阶段的独立调度中，设计了兼顾适应度和种群多样性2种能力的评估机制，保证种群的多样性。在第②、③阶段协同调度中，设计惩罚因子引入算法，能够有效避免不满足目标约束的种群出现。仿真结果表明：与传统的人工调度和遗传算法对比，所提算法调度加油车数量平均降低了27.6%和21.8%，能够为机场加油车调度提供有效的决策支持。
- 航空运输 /
- 机场 /
- 航班保障 /
- 改进遗传算法 /
- 加油车调度
Abstract:
To address the issue of inefficient refueling vehicle scheduling during airport flight support operations, this study establishes dual constraints for flight refueling time windows and permissible commencement time windows while prioritizing flight safety. It creates three integer programming models that optimize refueling vehicle allocation under these two limitations, standardizes stand designations and apron positions, and looks at key variables in three operational situations. According to the actual operation of the airport, a genetic optimization algorithm with elite strategy was proposed to solve the model according to the actual operation of the airport. In the first stage of independent scheduling, an evaluation mechanism that takes into account the two abilities of adaptability and population diversity was designed to ensure the diversity of the population. In the second and third stages of collaborative scheduling, a penalty factor introduction algorithm is designed, which can effectively avoid the emergence of populations that do not meet the target constraints. The simulation results show that compared with the traditional manual scheduling and genetic algorithm, the number of dispatched fuel trucks is reduced by 27.6% and 21.8% on average, which can provide effective decision support for airport fuel truck scheduling.
- air transportation /
- airport /
- flight guarantee /
- improved genetic algorithm /
- refueling vehicle scheduling

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图 1 加油车工作路线示意

Figure 1. Schematic diagram of the working route of the refueling truck

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图 2 位于2个不同机坪的停机位之间的行驶路线和距离

Figure 2. Travel route and distance between parking stands located on two different aprons

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图 3 时间窗口示意

Figure 3. Schematic diagram of the time window

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图 4 本文改进的带精英策略的遗传算法流程

Figure 4. Flowchart of genetic algorithm with elite strategy improved in this paper

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图 5 机场机位分布示意

Figure 5. Schematic diagram of airport stands

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图 6 T1航站楼迭代结果

Figure 6. Iterative results of T1 terminal

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图 7 T2航站楼迭代结果

Figure 7. Iterative results of T2 terminal

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图 8 T1、T2航站楼迭代结果

Figure 8. Iterative results of T1 and T2 terminals

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图 9 T1、T2、T3航站楼迭代结果

Figure 9. Iterative results of T1, T2, and T3 terminals

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图 10 实验对比

Figure 10. Experimental comparison

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图 11 最优个体适应度曲线

Figure 11. Optimal individual fitness curve

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表 1 航班计划

Table 1. Flight schedule

航班号	航班性质	机型分类	分配停机位	推出时刻	机型最小过站时间/min	最长可加油时间/min	旅客登机时间/min	加油量/kL
CA4132	离港	C	552	7:05	65	50	15	22
NH160	离港	D	520	14:20	75	50	25	50
TG615	离港	E	512	17:05	90	55	35	160
LH721	离港	F	509	10:30	90	50	40	250

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表 2 航班飞机类型加油方式对比

Table 2. Comparison of aircraft types and refueling methods for flights

机型信息	最小油量/L	加油速率/（L·s⁻¹）	单车加油时间/min	允许加油时间/min	至少需要加油车数量
C	15 000	10	25	[35,60]	1
D	35 000	15	38.8	[50,55]	1
E	140 000	30	77.8	[40,55]	2
F	250 000	40	104	50	3

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表 3 T1航站楼调度结果

Table 3. T1 terminal scheduling results

加油车编号	调度结果（航班编号）
1号加油车	5 9 12 17 24 26 28 43 47 53 55 57 62 65 71 76
2号加油车	2 6 8 11 13 16 20 30 35 38 45 49 51 54 58 63 67 78 81
3号加油车	10 15 18 19 21 23 29 33 37 39 41 44 46 48 50 52 60 69 74
4号加油车	1 3 4 7 14 22 25 27 31 32 34 36 40 42 56 59 61 64 66 68 70 72 73 75 77 79 80

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表 4 T2航站楼调度结果

Table 4. T2 terminal scheduling results

加油车编号	调度结果（航班编号）
1号加油车	4 12 19 23 27 34 52 54 62 67 76 82 84 90 94 101 103 114 133 135 140 143 146 155 162 170 172 185 207 209 211 213 216 222 229 236
2号加油车	113 122 138 145 148 165 167 175 177 181 186 198 200 202 217 219 226 228 237 251
3号加油车	2 6 15 29 32 38 39 41 57 63 74 79 86 91 95 97 100 116 124 126 128 134 157 160 163 168 182 192 215 225 234 240 243 260
4号加油车	3 13 17 45 55 64 72 77 87 99 105 107 111 121 125 127 136 151 174 183 189 196 199 212 223 235 238 252 255 261 263 265
5号加油车	5 7 16 22 35 43 48 51 58 60 81 115 139 153 164 166 193 208 214 218 220 227 248 256
6号加油车	14 21 24 30 33 36 40 46 53 66 70 104 108 117 137 154 156 158 169 171 178 190 203 206 210 221 232 244 246 249 254 264 267 269
7号加油车	1 10 26 28 44 47 59 69 71 88 93 96 102 106 109 119 129 132 147 149 176 179 197 241 245 266 271
8号加油车	8 20 31 50 56 61 68 83 98 112 118 123 131 142 144 152 159 161 173 180 184 187 195 201 204 224 231 239 242 247 250 253 258 262 270
9号加油车	9 11 18 25 37 42 49 65 73 75 78 80 85 89 92 110 120 130 141 150 188 191 194 205 230 233 257 259 268

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表 5 T1、T2航站楼调度结果

Table 5. Scheduling results of T1 and T2 terminals

加油车编号	调度结果（航班编号）
1号加油车	19 47 106 137 162 163 177 178 213 222 267 290 306 324 351
2号加油车	29 39 89 115 117 132 165 198 214 239 286
3号加油车	21 72 83 94 99 218 252 271 277 319 323
	
28号加油车	27 64 120 121 167 170 236 253 295 313 339 349
29号加油车	18 81 122 154 181 207 232 251 298 308 338 348
30号加油车	8 17 68 114 131 156 158 212 242 283 305 333 352

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表 6 T1、T2、T3航站楼调度结果

Table 6. Scheduling results of T1, T2, and T3 terminals

航班类型	加油车编号	调度结果（航班编号）/C、D型航班
C、D型	1号加油车	53 149 162 226 227 240 260 319 334 349 374 470 495 512 558 576
	2号加油车	50 126 188 193 215 257 278 309 331 369 383 406 454 459 468 497 523 541 593
		
	35号加油车	27 46 204 292 370 458 476 493 520 590 605
	36号加油车	43 68 75 79 84 110 113 118 124 127 142 207 228 231 237 315 339 342 352 355 373 387 450 466 486 587
E、F型	37号加油车	147 156 160 195 200 246 248 286 390 397 420 430 465 496 506 530 572 581 595
	38号加油车	77 85 155 171 191 222 251 259 325 353 362 372 448 484 535 543 554 564 566 574 602
		
	44号加油车	86 114 139 175 183 341 393 402 415 427 456 464 503 524 575
	45号加油车	120 133 217 242 271 351 429 600

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表 7 不同调度方案结果对比

Table 7. Comparison of the results from different scheduling schemes

调度类型	T1航站楼用车数量	T2航站楼用车数量	T1、T2航站楼用车数量	T1、T2、T3航站楼用车数量
人工调度	6	19	35	50
遗传算法	5	17	34	49
改进遗传算法	4	9	30	45

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