Benchmark for the scheduling problems of airport ground support operations and a case study

被引:0
|
作者
Cai, Zhihao [1 ]
Gao, Wanru [1 ,2 ,3 ]
Feng, Ran [1 ]
Li, Yafei [1 ,2 ,3 ]
Xu, Mingliang [1 ,2 ,3 ]
机构
[1] Zhengzhou Univ, Sch Comp & Artificial Intelligence, Zhengzhou 450001, Henan, Peoples R China
[2] Minist Educ, Engn Res Ctr Intelligent Swarm Syst, Zhengzhou 450001, Henan, Peoples R China
[3] Natl Supercomp Ctr Zhengzhou, Zhengzhou 450001, Henan, Peoples R China
基金
中国国家自然科学基金;
关键词
Benchmark; Airport ground support operations; Heuristic algorithms; Multi-objective optimization; Performance assessment; OBJECTIVE OPTIMIZATION; HEURISTIC ALGORITHM; FERRY VEHICLE;
D O I
10.1016/j.asoc.2024.112555
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Airport ground support operations are critical services provided for aircraft after landing and before takeoff and have a great impact on airport management efficiency and aviation economics. Recently, there has been a growing interest in addressing scheduling issues related to airport ground support operations. However, the lack of publicly available and standardized benchmarks presents a challenge for researchers aiming to conduct comprehensive studies as well as effectively benchmark various solution algorithms. Hence, in this paper, an algorithm to generate diverse instances has been proposed. Using this algorithm, a set of benchmarks has been organized. Particularly, a set of features and an iterative selection mechanism are proposed to increase the diversity of generated instances. To validate that the benchmark can be supported to investigate the scheduling problems of airport ground support operations and reveal different performances among various algorithms, a multi-objective optimization problem is introduced as a case study. Then, five heuristic algorithms are evaluated on different sets of instances. Finally, the experimental results demonstrate that the benchmark is capable of distinguishing various algorithms even on different metrics.
引用
收藏
页数:14
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