Abstract: In the civil aviation industry,one of the keys to improvingpassenger satisfaction lies in understanding travelers’ personalized needs and providing customized travel services,particularly in flight seat allocation.However,achieving this goal faces two major challenges: how to accurately model passenger preferences and how to allocate seats rationally.Traditional methods often require explicit knowledge of passengers’ true preferences,yet current strategies such as paid seat selection and first-come-first-served approaches struggle to fully satisfy passenger demands.To address this issue,it is essential to consider seat availability,spatial correlations,and social relationships among passengers.This paper proposes a novel solution that models passenger preferences from both individual and social dimensions,framing seat allocation as a combinatorial optimization problem aimed at maximizing the fulfillment of individual and social preferences while adhering to business rules and passenger value.The solution employs an iterative local search algorithm to optimize seat allocation.Experimental results demonstrate that this method effectively models passenger seat preferences and significantly enhances overall flight satisfaction.

Key words: Seat allocation optimization, Passenger preference modeling, Combinatorial optimization