A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm

Cai, Xinye; Sun, Wenxue; Mısır, Mustafa; Tan, Kay Chen; Li, Xiaoping; Xu, Tao; Fan, Zhun

doi:10.1109/tcyb.2019.2956974

Cited by 20 publications

(3 citation statements)

References 34 publications

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“…In addition, GAP tries to distribute gates to planes while taking airport operational effectiveness and traveler pleasure into account. Cai et al ( 2019 ) proposed CBR-GAM to solve the difficulties of traveler walking distance and high gateway allocation costs. The two objectives that need to be maximized, while meeting the restrictions on the constrained number of planes allocated to the apron, are the overall walking path of travelers and the overall robust cost of the gateway allocation.…”

Section: Related Workmentioning

confidence: 99%

Optimizing airport slot scheduling problem using optimization algorithms

Shambour

Abu-Hashem

2023

Soft Comput

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The primary objective of airport management worldwide is always to make it easier to provide transportation services and minimize latency. This could be accomplished by controlling the movement of travelers through the airport's different checkpoints for passports, baggage handling, customs, and both departure and arrival lobbies. As one of the biggest passenger terminals around the world and among the most attractive destinations for visitors during the Hajj pilgrimage, this paper concentrates on enhancing the movement of travelers in the King Abdulaziz International Airport's pilgrimage station in the Kingdom of Saudi Arabia. Several optimization methods are used to better schedule the phases within the airport terminals as well as the assignment of arriving flights to vacant airport portals. These include the differential evolution algorithm (DEA), harmony search algorithm, genetic algorithm (GA), flower pollination algorithm (FPA), and black widow optimization algorithm. The findings demonstrated the potential sites for the development of airport stages, which may assist decision-makers in improving operational efficiency in the future. The simulation results showed that GA was more efficient in most of the experiments than the alternative algorithms for small population sizes in terms of the quality of the solutions obtained and the convergence rates. In contrast, DEA performed better in the larger population sizes. The outcomes also showed that FPA performed better than its rivals in identifying the optimal solution in terms of the overall duration of passenger waiting time.

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Section: Related Workmentioning

confidence: 99%

Optimizing airport slot scheduling problem using optimization algorithms

Shambour

Abu-Hashem

2023

Soft Comput

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“…Since the relationship between outbreak controls and transfer claims was not considered, the optimal results might not be yielded in actual operations. Recent studies focused on the multiobjective optimization of gate assignments [36,37]. In the optimization goal of gate assignment research, Cai et al [36] modeled the GAP as a biobjective constrained optimization problem, where the two objectives were the total walking distance of passengers and the total robust cost of the gate assignment.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Recent studies focused on the multiobjective optimization of gate assignments [36,37]. In the optimization goal of gate assignment research, Cai et al [36] modeled the GAP as a biobjective constrained optimization problem, where the two objectives were the total walking distance of passengers and the total robust cost of the gate assignment. Furthermore, Bi et al [37] solved the GAP, where the objective is to maximize the number of passengers through a jetway.…”

Section: Literature Reviewmentioning

confidence: 99%

Cost-Effective Flight Sequencing and Gate Assignment Considering Transfer Time under Pandemic Conditions

Xiao

Liu

Chien

et al. 2023

Journal of Advanced Transportation

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An efficient hub-and-spoke network (HSN) can reduce operating costs and passenger delays at hubs through proper sequencing of flights and assignment of gates. Typically, batches of flights are scheduled to arrive within brief time windows. By considering aircraft sizes/loads and locations of the available gates, there is a considerable potential for reducing the total cost. During pandemic conditions, passenger transfer time and aircraft dwell time significantly increased because of outbreak controls (e.g., COVID-19 and its variant). In addition to walking time between connecting flights, there is a significant delay for the airport staff to validate passengers’ proper travel documents. The objective of this study is to minimize the total cost by optimizing the flight sequencing and gate assignment and by considering the realistic transfer delay under pandemic situations. A genetic algorithm with an elite selection strategy is developed to search for the optimal solution, which significantly reduces the total cost by 25% compared with that under existing operations, and the relations between optimized solutions and various model parameters are explored.

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Column generation based solution for bi-objective gate assignment problems

Daş,

Gzara

2024

Math Meth Oper Res

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A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm

Cited by 20 publications

References 34 publications

Optimizing airport slot scheduling problem using optimization algorithms

Optimizing airport slot scheduling problem using optimization algorithms

Cost-Effective Flight Sequencing and Gate Assignment Considering Transfer Time under Pandemic Conditions

Column generation based solution for bi-objective gate assignment problems

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