考虑旅客选择行为的航班供需适配优化研究OA

To alleviate the mismatch between flight supply and passenger demand,this paper proposes an optimization model for flight supply-demand alignment that incorporates passenger choice behavior.Based on 519 valid choice experiment observations,a Multinomial Logit(MNL)model is employed to characterize the heterogeneous preferences of business and leisure passengers regarding departure time,ticket price,aircraft type,and flight durations.These preferences are translated into differenti-ated flight demands at the time-slot level to accurately reflect the market's behavioral responses to flight supply.First,considering multiple constraints such as flight schedule,aircraft assignment,and aircraft maintenance,a bi-objective optimization model is constructed.This model aims to optimize flight schedule allocations and aircraft assignments to minimize both the deviation in market demand fulfillment and operational costs.Second,a hybrid Greedy-Genetic Algorithm(GGA)is adopted to solve the model.By combining the global search capability of a Genetic Algorithm(GA)with the local repair and optimization abilities of a greedy strategy,this approach ensures optimization efficiency and high solution quality.Finally,a case study based on a one-week flight schedule from Airline A is con-ducted.The results indicate that the optimization scheme significantly improves the match between flight supply and demand,reducing the deviation in market demand fulfillment by 34.3%and lowering operational costs by 12.1%.Furthermore,flight resource utilization is enhanced,and the flight plan's capacity to accommodate passenger demand is notably improved,particularly during high-demand pe-riods.By comprehensively accounting for the relationships among flight schedules,aircraft types,and passenger demand,the optimization model ensures both the economic viability and operational feasibil-ity of the flight plan.Overall,the proposed optimization model,which integrates passenger choice be-havior,holds substantial application value for enhancing the utilization efficiency of flight resources and market responsiveness.