Model And Algorithm For Flight Recovery Decision Problems

Due to bad weather conditions,unexpected aircraft failures and air traffic control,the normal operation of airlines is often disturbed,resulting in the consequence that flights can't be carried out as planned.Abnormal flights not only bring inconvenience to passengers,but also cause economic losses to the company thus affecting the corporate image.When abnormal flights occur,airlines will take a series of temporary measures,such as canceling flights,delaying flights,ferrying flights and even changing routes,to make the flight operation back to normal as soon as possible and minimize its losses as much as possible.Therefore,the decision-making of abnormal flight recovery has been highly valued by airlines,as well as a hot spot focused and researched by Aviation Operations Research Academia continuously.In this paper,both the model and algorithm of abnormal flight recovery decision-making are studied,especially works as the below listed two aspects are accomplished in detail.Firstly,based on the classical model,the cruise speed adjustment of aircraft is integrated into the decision-making optimization problem as a new decision-making method,constructing a decision-making model based on time-band approximation network.This model is a mixed integer non-linear programming.In view of the complexity of the model,combined with the actual operation characteristics and model structure,this paper reconstructs the model by decomposing the mixed integer non-linear programming into several linear programming,and solving it by LINGO software.The results of an example verify the effectiveness and practicability of the model and algorithm.Secondly,the application scope of the new model is extended to multi-aircraft in this paper,and the spillover costs caused by the exchange of different types of aircrafts are increased in the objective function,and the passenger disappointment rate is added to the constraints.An example is analyzed by using heuristic algorithm.The result shows that the model and algorithm possess effectiveness in solving the problem of abnormal flight recovery.