Flight scheduling and maintenance base planning
Management Science
The fleet assignment problem: solving a large-scale integer program
Mathematical Programming: Series A and B
Decision support for airline system operations control and irregular operations
Computers and Operations Research
Daily aircraft routing and scheduling
Management Science
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
The Four-Day Aircraft Maintenance Routing Problem
Transportation Science
The Aircraft Maintenance Routing Problem
Operations Research
Flight String Models for Aircraft Fleeting and Routing
Transportation Science
Airline Fleet Assignment with Time Windows
Transportation Science
Improving Crew Scheduling by Incorporating Key Maintenance Routing Decisions
Operations Research
A Stochastic Programming Approach to the Airline Crew Scheduling Problem
Transportation Science
Integrated Airline Fleet and Crew Robust Planning
Transportation Science
Transportation Science
Disruption management in the airline industry-Concepts, models and methods
Computers and Operations Research
A multi-objective approach for robust airline scheduling
Computers and Operations Research
Modifying lines-of-flight in the planning process for improved maintenance robustness
Computers and Operations Research
Computers and Operations Research
Robust planning of airport platform buses
Computers and Operations Research
Solving a robust airline crew pairing problem with column generation
Computers and Operations Research
An Optimization Approach to Airline Integrated Recovery
Transportation Science
Reallocation problems in scheduling
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
An integrated scenario-based approach for robust aircraft routing, crew pairing and re-timing
Computers and Operations Research
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Airlines typically construct their schedules assuming that every flight leg will depart and arrive as planned. Because this optimistic scenario rarely occurs, these plans are frequently disrupted and airlines often incur significant costs in addition to those originally planned. Flight delays and schedule disruptions also cause passenger delays and disruptions. A more robust plan can reduce the occurrence and impact of these delays, thereby reducing costs. In this paper, we present two new approaches to minimize passenger disruptions and achieve robust airline schedule plans. The first approach involves routing aircraft, and the second involves retiming flight departure times. Because each airplane usually flies a sequence of flight legs, delay of one flight leg might propagate along the aircraft route to downstream flight legs and cause further delays and disruptions. We propose a new approach to reduce delay propagation by intelligently routing aircraft. We formulate this problem as a mixed-integer programming problem with stochastically generated inputs. An algorithmic solution approach is presented. Computational results obtained using data from a major U.S. airline show that our approach can reduce delay propagation significantly, thus improving on-time performance and reducing the numbers of passengers disrupted. Our second area of research considers passengers who miss their flight legs due to insufficient connection time. We develop a new approach to minimize the number of passenger misconnections by retiming the departure times of flight legs within a small time window. We formulate the problem and an algorithmic solution approach is presented. Computational results obtained using data from a major U.S. airline show that this approach can substantially reduce the number of passenger misconnections without significantly increasing operational costs.