A Novel Model and Decomposition Approach for the Integrated Airline Fleet Assignment, Aircraft Routing, and Crew Pairing Problem

Shengzhi Shao (), Hanif D. Sherali () and Mohamed Haouari ()
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Shengzhi Shao: Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia 24061
Hanif D. Sherali: Grado Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia 24061
Mohamed Haouari: Department of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar

Transportation Science, 2017, vol. 51, issue 1, 233-249

Abstract: Given a daily flight schedule and a set of aircraft fleets, the airline scheduling problem assigns individual aircraft and groups of crew to each flight based on specific considerations of aircraft maintenance requirements and crew work rules, respectively. Traditionally, this problem has been sequentially broken down into several stages, where the fleet assignment problem, which is solved first, partitions the entire flight network into subnetworks according to fleet types, followed by respectively solving the aircraft routing and crew pairing problems to generate suitable aircraft and crew rotations. However, this sequential approach ignores the interdependencies among the stages, leading to suboptimal, or even infeasible, solutions. In this paper, we propose an integrated model and solution approach that incorporates the fleet assignment (with itinerary-based demands), aircraft routing, and crew pairing problems within a single framework. We solve the resulting formulation of the problem by using a Benders decomposition approach, along with several acceleration strategies. Computational results obtained by using real-life data from a major U.S. airline demonstrate the benefits of the integrated approach.

Keywords: integrated airline scheduling problem; mixed-integer linear program; Benders decomposition; deflected subgradient optimization; reformulation-linearization technique (RLT); branch-and-price (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (8)

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