A robust strategy to address the airport gate assignment problem considering operators' preferences. (June 2022)

• Record Type: Journal Article
• Authors: She, Yaqian; Zhao, Qiuhong; Guo, Renyong; Yu, Xianrui
• Is Part Of: Computers & industrial engineering. Volume 168(2022)
• Publication Date: 2022-06
• Subjects: Airport gate assignment problem (AGAP) -- Operators' preferences -- Robustness -- TPMC-NSGA II algorithm; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108100
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Flight activities (arrival, parking, and departure) are assigned to different gates. A multi-objective integer programming model is proposed. A robust strategy is developed by considering the airport operators' preferences. The Monte Carlo based NSGA-II (TPMC-NSGA II) algorithm is designed. Abstract: The airport gate assignment problem (AGAP) has been well studied in the field of airport transportation planning and operations management. For airport operators, it is important to assign flight activities to limited gates economically, and the robustness of the assignment is also a key issue. In this paper, we address the problem of assigning a number of flight activities, including arrival, parking, and departure, to different gates during the operating period. A robust strategy is developed by considering the airport operators' tow-averse attributes. To solve the problem, firstly, a multi-objective integer programming model is proposed. There are two objectives in the model, one is to maximize the operators' preferences characterized by scores, and the other is to minimize robustness cost caused by the changes of flight schedule. Secondly, a two-phase Monte Carlo based NSGA-II (TPMC-NSGA II) algorithm is designed, which effectively combines the Monte Carlo characters and the NSGA-II algorithm. Furthermore, a set of computational analyses are conducted. The results show that the proposed model and algorithm are capable of solving the airport gate assignment problem with an economical, robust, and preferred output.