The airport gate assignment problem: A Branch-and-Price Approach for improving utilization of jetways

被引:14
作者
Bi, Jun [1 ,2 ]
Wang, Fujun [1 ]
Ding, Cong [1 ]
Xie, Dongfan [1 ]
Zhao, Xiaomei [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol C, Beijing 100044, Peoples R China
关键词
Gate assignment; Operation research; Branch and price; Airport operation; OPTIMIZATION; ALGORITHM; SEARCH; MODELS; SOLVE;
D O I
10.1016/j.cie.2021.107878
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With the development of the civil aviation industry, airports' parking space resources, especially those with jetways, become increasingly scarce. The airport gate assignment problem (AGAP) is a critical issue in airport operation management. When the number of flights is large, solving this situation is challenging. Therefore, designing an efficient gate assignment methodology is very important. This paper considers several significant constraints and aims to maximize the number of passengers using jetways, which is not fully considered in the existing research. A model with gate plans (possible scheme combinations) as decision variables is established, which effectively reduces the number of constraints. However, considering that the scale of this problem is still quite large, the Branch- and-Price algorithm (BAPA) is used to solve the model. The solving speed is improved by adding a heuristic search with a certain probability in each search node. The model's performance is verified by using the actual flight data of Kunming Changshui International Airport, China. The experimental results show that the method of this paper can achieve a 12.71 % increase in the optimization goal compared to the current computer-assisted manual allocation. In terms of finding the optimal and satisfactory solution, the feasibility and effectiveness of this method are verified by comparing with the commercial solver CPLEX, Tabu Search (TS) algorithm, improved Adaptive Parallel Genetic (APGA) algorithm, and Greedy algorithm (GA).
引用
收藏
页数:13
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