Abstract
The airline recovery problem involves aircraft, crew and passenger networks impacted by disruptions. Models to solve the problem consider one or more of these networks, on an integrated way or not. It belongs to the NP-hard class, even considering only one network. This work presents a math-heuristic to solve the problem integrating the aircraft and the passenger networks. A model to restore the aircraft network with minimum cost was also developed. These two models compose a framework which permits the airline to obtain the cost impact of including the passenger network in the recovery problem. Both models were tested with real world ROADEF instances using an Intel i7 microcomputer (16Gb of RAM) and a high-performance cluster node (HPC) with 512 GB of RAM. The microcomputer solved instances with up to 85 aircraft and 276 impacted flights in less than 30 minutes (imposed limit). The faster high-performance server reached solutions with minimum gap of 0 to 0.7% for the instances with higher number of flights. Total costs considering aircraft and passenger networks were very close to the aircraft network recovery results, showing a cost compensation which highlights the importance of solving the recovery problem integrating aircraft and passenger networks.
Highlights
1.1 Airline Opera onal PlanThe airline operational plan starts long before a light takes off
The models were implemented in Python 3.7, C++ (Step 2 only), Gurobi 8.1.1. They were tested thanks to a set of real world instances created by ROADEF for an operations research chalenge in 2009 (Palpant et al, 2009)
The following information were considered for each instance: initial programming in terms of the number of lights per day of the recovery window; and numbers and details of the aircraft leet, of the airports and of the affected passenger itineraries during the recovery window
Summary
1.1 Airline Opera onal PlanThe airline operational plan starts long before a light takes off. Each of these three schedules can be represented by a resource network. They must be synchronized so that the lights operate as planned and as ef iciently as possible. An airline disruption occurs when at least one of the required resources to operate a light is not available and ready at the light’s planned departure time. It may affect the departure of one or more lights. Even minor disruptions can create ripple effects across the network and quickly affect the rest of the light network
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