US Airways Automates Its Weekend Fleet Assignment

Kontogiorgis, Spyros; Acharya, Suresh

doi:10.1287/inte.29.3.52

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…The fruits of research in this field have been used by airlines to improvement their operations and increase profit. For instance, algorithms for solving fleet assignment problems have been used by American Airlines [17], Delta Airlines [25], and US Airways [26].…”

Section: A Aircraft Allocationmentioning

confidence: 99%

Simultaneous aircraft allocation and mission optimization using a modular adjoint approach

Hwang

Roy

Kao

et al. 2015

56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

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The aircraft design optimization problem is typically formulated to maximize performance at a small number of representative operating conditions. This approach makes simplifying assumptions such as ignoring the climb and descent phases, but they can be avoided by performing simultaneous designmission-allocation optimization with surrogate models for the aircraft design disciplines. As a first step towards this goal, this paper presents a method for simultaneous allocation-mission optimization. We integrate aerodynamic and propulsion surrogates, a mission analysis tool, and allocation models within a computational framework that automates solving the coupled simulation and computing derivatives using the adjoint method for gradient-based optimization. We solve the mixed-integer allocation-mission optimization problem by using the linear allocation-only optimization to generate a good starting point and applying the branch-and-bound method to find an optimum for the mixedinteger nonlinear allocation-mission problem. The results show that this approach efficiently finds good local optima with, on average, roughly 10 node evaluations in the branch-and-bound method and most of the continuous optimizations converging almost immediately. The results show that adding next-generation aircraft to a fleet yields a 200-400 % profit increase for a 3-route test problem.

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Section: A Aircraft Allocationmentioning

confidence: 99%

Simultaneous aircraft allocation and mission optimization using a modular adjoint approach

Hwang

Roy

Kao

et al. 2015

56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference

View full text Add to dashboard Cite

show abstract

“…Because of the huband-spoke nature of operations and large fleet sizes, it is always possible to obtain a feasible tail routing from the assignment recommended by the model. Kontogiorgis and Acharya [4] developed schedule planners for US Airway that balanced between meeting weekend passenger demand, which is different from weekday demand, and also minimize the costs of realigning airport facilities and personnel that we would incur by changing fight patterns too much. They built a specialized fleetassignment model and integrated it into a graphical environment for schedule development.…”

Section: Literature Reviewmentioning

confidence: 99%

Intercity Bus Scheduling for the Saudi Public Transport Company to Maximize Profit and Yield Additional Revenue

Hasan¹,

Hammad²

2010

JSSM

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The Saudi Public Transport Company (SAPTCO) intercity bus schedule comprises a list of 382 major trips per day to over 250 cities and villages with 338 buses. SAPTCO operates Mercedes 404 SHD and Mercedes 404 RI-IL fleet types for the intercity trip. The fleet assignment model developed by American Airlines was adapted and applied to a sample of the intercity bus schedule. The results showed a substantial saving of 29% in the total number of needed buses. This encourages the decision makers at SAPTCO to use only Mercedes 404 SHD fleet type. Hence, the fleet assignment model was modified to incorporate only one fleet type and applied to the sample example. Due to the increase in the problem size, the model was decomposed by stations. Finally, the modified decomposed model was applied to the whole schedule. The model results showed a saving of 16.5% in the total number of needed buses of Mercedes 404 SHD. A sensitivity analysis was carried out and showed that the predefined minimum connection time is critical for model efficiency. A modification to the connection time for 11 stations showed a saving of 14 more buses. Considering our recommendation of performing a field study of the trip connection time for every station, the expected saving of the total number of needed buses will be about 27.4% (90 buses). This will yield a net saving of 16.44 million Saudi Riyals (USD 4.4 million) per year for SAPTCO in addition to hiring new employees. The revenue analysis shows that these 90 surplus buses will yield about USD 20,744,000 additional revenue yearly

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“…For a regular schedule, the airline companies have to solve a more complicated weekly fleet assignment problem [10][11][12][13]. In a daily fleet assignment, modifications for weekend flights have to be made in a separate step [14,15].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Optimization of Fleet Assignment: A Case Study in Turkey

Özdemi̇r

Başlıgil

Nalbant

2011

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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Since poor fleet assignment can cause a great increase in costs for airline companies, a solution of the type 'right fleet for the right flight' would be very useful. In this paper, a fleet assignment model is set up using the data of the largest Airline Company in Turkey, Turkish Airlines. The aim of this model is to assign the most appropriate fleet type to flights while minimizing the cost and determining the optimal number of aircraft grounded overnight at each airport. We set up a model with constraints with thinking all airline operations and solve our problem using integer linear programming. Finally, we get an optimum solution which minimizes the total cost while assigning the fleet type to the flight leg. Using optimization software (Lindo 6.1), the solution to this problem generates a minimum daily cost of fleet assignment.

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US Airways Automates Its Weekend Fleet Assignment

Cited by 9 publications

References 6 publications

Simultaneous aircraft allocation and mission optimization using a modular adjoint approach

Simultaneous aircraft allocation and mission optimization using a modular adjoint approach

Intercity Bus Scheduling for the Saudi Public Transport Company to Maximize Profit and Yield Additional Revenue

Optimization of Fleet Assignment: A Case Study in Turkey

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