Title of article :
An Integrated Model for Crew, Aircraft and Passenger Recovery Problem: A Real Case Study
Author/Authors :
Khiabani ، Amir Department of Industrial Engineering - Islamic Azad University, South Tehran Branch , Rashidi Komijan ، Alireza Department of Industrial Engineering - Islamic Azad University, Firoozkooh Branch , Ghezavati ، Vahidreza Department of Industrial Engineering - Islamic Azad University, South Tehran Branch , Mohammadi Bidhendi ، Hadi Department of Industrial Engineering - Islamic Azad University, South Tehran Branch
Abstract :
Airlines try to reduce costs by improving the quality of their operational schedules. However, numerous uncontrollable factors make disruptions inevitable. A flight delay or cancellation caused by disruption may spread throughout the network and increase the operational costs by affecting the schedule of other flights, including aircraft, crew, and passengers’ itineraries. While previous researchers have focused on one of these aspects or sequential approaches, the resulted solutions cannot lead to a reliable operational solution due to the complex relationships between these factors in practice. Therefore, integrated recovery approaches are highly essential. The main objective of this research is to provide a fully integrated recovery model that contains various recovery scenarios to tackle the disruption and delay propagation with more flexibility and acceptable solution time. So, an integrated model for crew, aircraft, and passenger recovery problem is proposed in this paper. The proposed model is formulated as MILP, based on individual flight legs to achieve a more accurate schedule with better recovery solution. Options such as aircraft reassignment, crew swapping, reassignment of passengers, and ticket refunds are considered as alternatives to face disruption. Moreover, the considerations related to crew rest-time and maintenance requirements are also included in the model. Due to the NP-Hard nature of the problem, the Genetic algorithm is used as the solution approach successfully for the real-world data to limit delay propagation on various random flights.
Keywords :
Integrated Airline Recovery Problem , Mathematical Modeling , Delay Propagation , Genetic Algorithm
Journal title :
Advances in Industrial Engineering
Journal title :
Advances in Industrial Engineering