Research On Multi-Objective Optimization Of Ground Holding Strategy Considering Passenger Satisfaction And Carbon Emissions

With the rapid development of the civil aviation transportation industry,the number of routes and flights opened have increased.The contradiction between the service efficiency of airport flights during peak hours and the limited airport capacity has become increasingly prominent.The most direct manifestation is the frequent occurrence of flight delays,which leads to many problems such as the decline in passenger satisfaction,the increase in fuel consumption and carbon emissions,resulting in huge economic losses.The ground holding strategy is an important control measure for air traffic flow management,and an effective means to alleviate air traffic congestion and improve flight operation efficiency.Therefore,in order to solve the above problems,it is of great significance to carry out research on the ground waiting problem.Based on comprehensive research on related achievements at home and abroad,this paper has carried out in-depth research on the model construction,algorithm solution and algorithm optimization of the ground holding problem.The main work and research results are summarized as follow:(1)Summarize relevant domestic and foreign literature and research results.This paper mainly summarizes the research status of the ground-holding problem and the solution algorithm.It is found that the existing research on the ground holding problem focuses on the single goal optimization of minimizing the total delay time,but in actual operation,passengers and fuel consumption also need to be considered as the key factors.Thus,it puts forward the theoretical and practical significance of the research.(2)Constructed a multi-objective optimization problem model considering flight delay time,passenger satisfaction and carbon emissions,and made a unified operation optimization for all incoming and outgoing flight slots at the target airport in the system,aiming to make full use of airport time slice resources and reduce flight delays and its negative effects.(3)Based on non-dominated genetic algorithm(NSGA-Ⅱ),a large-scale solution algorithm is designed for the multi-objective optimization problem constructed in this paper,and the importance of genetic control parameter optimization in solving largescale examples is considered.Therefore,combined with the optimal computing budget allocation(OCBA)to optimize the solution algorithm,and compared and analyzed the experimental results,the optimized algorithm has improved the quality of the solution and the number of iterations.(4)A case experiment with actual flight information is carried out.Taking Beijing Capital International Airport,Shanghai Hongqiao Airport and Guangzhou Baiyun Airport as examples to verify,through comparative analysis,the rationality and effectiveness of the model and algorithm are proved.(5)Summarize the full text and propose future research directions.Summarize the full text objectively,and point out the directions for future expansion and in-depth research in conjunction with related research in this field.