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To improve the efficiency of gate reassignment and optimize the plan of gate reassignment,the concept of disruption management is introduced,and a multi-objective programming model for airport gate reassignment is proposed.Considering the interests of passengers and the airport,the model minimizes the total flight delay,the total passengers′walking distance and the number of flights reassigned to other gates different from the planned ones.According to the characteristics of the gate reassignment,the model is simplified.As the multi-objective programming model is hard to reach the optimal solutions simultaneously,a threshold of satisfactory solutions of the model is set.Then a simulated annealing algorithm is designed for the model.Case studies show that the model decreases the total flight delay to the satisfactory solutions,and minimizes the total passengers′walking distance.The least change of planned assignment is also reached.The results achieve the goals of disruption management.Therefore,the model is verified to be effective.
To improve the efficiency of gate reassignment and optimize the plan of gate reassignment, the concept of disruption management is introduced, and a multi-objective programming model for airport gate reassignment is proposed. Considents of the interests of passengers and the airport, the model minimizes the total flight delay, the total passengers’ walking distance and the number of flights re-assign to other gates different from the planned ones. According to the characteristics of the gate reassignment, the model is simplified. As the multi-objective programming model is hard to reach the optimal solutions simultaneously, a threshold of satisfactory solutions of the model is set.Then a simulated annealing algorithm is designed for the model. Case studies show that the model reduces the total flight delay to the grace solutions, and minimizes the total passengers’walking distance.The least change of planned assignment is also reached. The results achieve the goals of disruption managem ent.Therefore, the model is verified to be effective.