Increasing stopover slack time can reduce flight delays, but it reduces aircraft utilization and economic benefits of airlines. This study comprehensively considers the aircraft utilization and flight delay issues, models the stopover slack time cost, and constructs a mathematical model with the goal of minimizing the stopover slack time cost and flight delay cost. According to the characteristics of the model, an improved adaptive large neighborhood search algorithm is designed, which includes three flight loop destruction operators and two repair operators. An adaptive operator selection strategy is used to improve the search efficiency, and a simulated annealing mechanism is used as the solution acceptance criterion to prevent the algorithm from falling into the local optimum. The experimental results show that the solution cost obtained by the proposed algorithm is reduced by an average of 14.5% compared to other algorithms; compared to the scheduling scheme with the goal of minimizing flight delays, the operating cost of this model is reduced by an average of 12.2%.