【摘要】 依据航班的进离港过程,提出了一种航班优先系数计算策略,使得延误损失在进离港航班之间的分配合理化;在此基础上建立了一种进离港地面等待问题(ADGHP)多目标优化模型,以实现延误损失和续航航班延误时间的多目标优化。针对问题模型的复杂性以及现有多目标遗传算法(MOGA)的不足,提出了一种引入局部搜索机制的多种群遗传算法对问题求解,并改进优秀个体迁移策略,实现多目标的协同优化。最后,以国内某机场进离港航班为算例,使用所提算法进行计算,并与其它典型算法的求解结果对比,实验结果表明了所提模型与算法的有效性。更多还原

【Abstract】 A strategy of computing flight priority coefficient was brought forward according to arrivaldeparture process,in order to assign delay cost between arrival flights and departure flights reasonably.Moreover,a multi-objective optimization model was proposed for Arrival-Departure Ground-Holding Problem(ADGHP),so as to achieve multi-objective optimization of minimizing delay cost and delay time of flights with continuation of the journeys.Due to the complexity of the model and inefficiency of existing MultiObjective Genetic Algorithm(MOGA),a multi-population multi-objective genetic algorithm was proposed for the model,which included with local search strategy,and improved elitist selection and individual migration strategy to realize multi-objective co-optimization.Finally the simulation was implemented with the data of arrival-departure flights from an airport in China.The experimental results show the validity of the proposed algorithm and model,comparing with the results of other representative algorithms.更多还原