Integrated intelligent recovery method for abnormal flights

Abstract

The invention discloses an integrated intelligent recovery method for abnormal flights. The integrated intelligent recovery method comprises the following steps: carrying out flight related data acquisition and input, model / algorithm parameter configuration and recovery scene configuration; establishing a mixed integer model of airplane path recovery, unit scheduling recovery and passenger travelrecovery on the basis of the input data and the set parameters, and performing solving by using an algorithm taking column generation as a core; and outputting adjustment plans of flights, airplanes and units and recovery plans of passengers according to calculation results, and counting various recovery situation evaluation indexes according to execution situations. By means of the technical means of establishing the optimization model, designing the optimization algorithm and the like, an integrated recovery scheme for large-scale abnormal flights can be provided in a short time.

Description

technical field [0001] The invention belongs to the technical field of air flight lines, and in particular relates to an integrated intelligent recovery method for abnormal flights. Background technique [0002] With the upgrading of transportation, air travel has become a mainstream choice. However, due to the harsh flight conditions, the probability of flight delay has become one of the main considerations for passengers to choose this mode of travel in addition to price. According to the 2019 Civil Aviation Industry Development Statistical Bulletin, passenger airlines across the country performed a total of 4.6111 million flights, of which 3.7652 million were regular flights. The average flight regularity rate was only 81.65%, and the average delay time was 14 minutes. In most cases, emergencies are unavoidable, and the resulting irregular flights not only damage the interests of passengers, but also damage the reputation and economic benefits of airlines. Therefore, it...

AI Technical Summary

Problems solved by technology

When the scale of the problem increases, business personnel cannot consider the recovery of thousands of flights through the human brain, and local optima are prone to occur. For example, some flights are restored quickly but more flights are at risk of being cancelled.

On the other hand, business personnel usually restore each resource sequentially, so the recovery correlation between each resource cannot be considered, resulting in the flight recovery plan formulated in the previous stage leaving little room for recovery of subsequent resources

In addition, due to the differences in professional knowledge and work experience of personnel, the results of different personnel's handling of the same emergency vary greatly

(2) The formulation of the plan takes a long time

Manual planning takes a long time

For large-scale abnormal flights, manually formulate plans for up to 6-8 hours, resulting in missing the best time for recovery of abnormal flights, increasing the total delay and cancellation rate of flights

(4) Low degree of personalization

Manual adjustments can be adjusted without violating the overall recovery goal, but cannot effectively respond to more detailed requirements that need to be considered overall, such as preferences for different recovery methods, etc.

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