Solving the Airline Recovery Problem By Using Ant Colony Optimization

In this paper an Ant Colony (ACO) algorithm is developed to solve aircraft recovery while considering disrupted passengers as part of objective function cost. By defining the recovery scope, the solution always guarantees a return to the original aircraft schedule as soon as possible which means least changes to the initial schedule and ensures that all downline affects of the disruption are reflected. Defining visibility function based on both current and future disruptions is one of our contributions in ACO which aims to recover current disruptions in a way that cause less consequent disruptions. Using a real data set, the computational results indicate that the ACO can be successfully used to solve the airline recovery problem.

Keywords:

Airline Scheduling , Disruption Management , Aircraft Recovery , Ant Colony Optimization Algorithm