En Route Speed Change Optimization for Spacing Continuous Descent Arrivals  
Marcus Lowther (Master student at Georgia Institute of Technology, United States of America)

Abstract: Continuous Descent Arrival (CDA) procedures have been shown to minimize the thrust required during landing, reducing noise, emissions, and fuel usage for commercial aircraft. Widespread implementation of CDA would result in significant reductions in environmental impact and airline operating costs. However, a significant barrier to system wide CDA implementation is the ability to merge and space CDA aircraft with required spacing so that the CDA is flown safely and the spacing of the aircraft does not incur significant additional fuel use from heading and speed changes. Thus, a method was developed to determine adjustments to cruise speeds while aircraft are en route, while achieving the spacing targets calculated by the Tool for Analysis of Separation and Throughput, and to optimize fleet wide fuel burn increase. The En route Speed Change Optimization Relay Tool solves the speed change problem quickly, while dividing the speed changes fairly across multiple airlines.

Integration of gate assignment and platform bus planning  
Guido Diepen (Ph.D. student at University of Utrecht, The Netherlands)

Abstract: In this paper we look at the gate assignment problem and the bus planning problem as they appear at Amsterdam Airport Schiphol (AAS). Furthermore, we consider the integrated version of these problems. Given the expected arrivals and departures for the next day, we aim at finding a robust solution, such that the amount of replanning due to deviations from the expected arrival and departure times is minimum. For the separate problems we present two similar integer linear programs (ILP) and solve the LP-relaxations through column generation. The generated columns and a set of additional columns are then used to solve the ILP. For the integrated approach we show how to link the models of the separate problems to form one large model. Computational results with real life data provided by AAS are promising and indicate that the algorithm is able to solve real-life instances within acceptable running times.

Airline Passengers’ Online Search and Purchase Behavior: New Insights from an Interactive Price Response Model  
Misuk Lee (Ph.D. student at Georgia Institute of Technology, United States of America)

Abstract: This paper develops a model of airline customers’ on-line search and purchase behavior using page-by-page clickstream data collected from a web-based Interactive Pricing Response (IPR) system that was implemented by Freedom Air, a former low cost subsidiary of Air New Zealand. The IPR system represents a new business model designed to stimulate demand by dynamically offering discounts to highly time-flexible travelers in a way that does not trigger price responses from competitors. A new model based on Markov-methods that incorporates reference price effects is proposed to capture the dynamics of customer search and purchase behaviors of these highly time-flexible leisure travelers. Empirical results show that higher search intensities and purchase conversions occur as the relative discounts increase. In addition, while product attributes displayed on the previous screen are highly correlated with product attributes displayed on the current screen, fundamental customer choices related to whether to continue shopping, to purchase, or not to purchase are driven predominately by the relative discount level displayed on the current screen. Simulations are used to illustrate how these highly-predictable search and purchase behaviors can be integrated back into the IPR system, effectively enabling firms to control conversion rates and the relative discount rate ranges offered in the market.

Block Time Estimation and Robust Airline Scheduling  
Yu-Ching Lee (Master student at University of Illinois, United States of America)

Abstract: Airline schedule development continues to remain one of the most challenging planning activity for any airline. An airline schedule comprises a list of flights and specifies the origin, destination, scheduled departure, and arrival time of each flight in the airline’s network. A critical component of the schedule development activity is the estimation of flight block-times, which depend on several factors. Many airlines estimate these block-times simply by using limited historical data, however, such techniques have not resulted in significantly improved on-time performance of the schedule during operations. Thus, from a passenger’s perspective, the service level guarantee of an airline’s network continues to be low. We first define two service level metrics for an airline schedule. The first one is similar to the on-time performance measure of the U.S. Department of Transportation and we define it as the flight service level. The second metric, called the network service level, is geared towards completion of passenger itineraries. We then develop a stochastic integer programming formulation that optimally perturbs a given schedule to maximize expected profit while ensuring the two service levels. We also develop a variant of this model that maximizes service levels while achieving desired network profitability. To solve these models we develop an efficient algorithm that guarantees optimality. Through extensive computational experiments, using real-world data, we demonstrate that our models and algorithms are efficient and achieve the desired trade-off between service level and profitability.

The Application of Semidefinite Programming to the Aircrew Scheduling Problem  
Leander Quiring (Master student at University of Waterloo, Canada)

Abstract: It is said that the world is shrinking every day. Passenger air travel, along with electronic communication, is undoubtedly one of the key factors responsible for this shrinking. To allow air traffic in the volumes we see today, quite a few extremely difficult problems had to be solved in the fields of structural engineering, aerodynamics, even marketing. In this paper, we examine one such problem, the aircrew scheduling problem, and how it is has been solved in industry. We then examine a Semi-Definite Programming (SDP) relaxation for the two phases of this problem and test it on three test cases. The results of these test cases are promising, and suggest that further research in this area might be very rewarding. We also suggest several practical areas in which this research might be directed and where SDP could be used in the airline industry.

Fairness in the Aircraft Landing Problem  
Maarten Soomer (Ph.D. student at VU University of Amsterdam, The Netherlands)

Abstract: The last few decades a lot of attention has been paid to Collaborative Decision Making (CDM) in Air Traffic Management. A lot of models are proposed in which information of stakeholders (mainly airlines) is used in some way to improve the decision process. When doing this, fairness becomes an important issue. However, it is not always clear what will be considered fair by the airlines involved. In this paper we will use the aircraft landing problem to illustrate various definitions of fairness, that stem from the use of airline preferences. In this problem, a landing order and feasible landing times have to be determined for a set of flights at a runway. The airlines cost and the various definitions of fairness are used as objective for the problem. Local search heuristics are introduced to solve these formulations. Numerical experiments using schedule data from a large European airport are used to evaluate how the fairness definitions and heuristics behave for real life problems. The results show that it is possible to achieve more fairness, while still obtaining considerable cost savings compared to the First Come First Served schedule. The heuristics obtain reductions of up to 26% in the root mean square deviation of the average cost per airline. The different heuristics show that schedules with different trade-offs between efficiency, cost, delay and fairness can be obtained. Hopefully, these results can be a starting point for discussing the fairness issues related to the introduction of CDM processes among air traffic stakeholders.

A Mixed Integer Programming Approach to the Aircraft Weight and Balance Problem  
Wouter Souffriau (Ph.D. student at KaHo Sint-Lieven, Belgium)

Abstract: The Aircraft Weight and Balance Problem (AWBP) is a real-world combinatorial optimisation problem in which an aircraft should be loaded with containers in such a way that the total cargo value is maximised. At the same time the centre of gravity should approach an optimal point. Flying optimally reduces fuel consumption and thus results in a financial and environmental gain. This paper introduces a mixed integer programming approach to solve the AWBP. Experimental results show that the model enables an increase of the cargo value compared to the result obtained by an experienced planner. Moreover, the mixed integer programming approach achieves better balanced solutions in only a few seconds.

Solving the Robust and Integrated Aircraft Routing and Crew Pairing Problem in Practice  
Oliver Weide (Ph.D. student at University of Auckland, New Zealand)

Abstract: We formulate an integrated aircraft routing and crew pairing model that yields solutions for both problems that incur small costs and are robust to typical stochastic variability in airline operations, i.e. effects of delays occurring in operations are minimised. We propose two new solution methods to solve the integrated model. The first approach is an optimisation based heuristic that is capable of generating good quality solutions quickly, the second approach utilises Dantzig-Wolfe decomposition to solve the integrated model to optimality. Using data from domestic Air New Zealand schedules, we evaluate the benefits of solving the integrated model on real world problem instances. Our solutions satisfy all rules imposed on aircraft routings and crew pairings and are ready to be implemented in practice. We obtain solutions that dramatically improve costs and robustness of solutions obtained by traditional methods. We also compare our approaches with an existing Benders decomposition approach.