Price of Airline Frequency Competition

Frequency competition influences capacity allocation decisions in airline markets and has important implications to airline profitability and airport congestion. Market share of a competing airline is a function of its frequency share and the relationship between the two is pivotal for understanding the impacts of frequency competition on airline business. Based on the most commonly accepted form of this relationship, we propose a game-theoretic model of airline frequency competition. We characterize the conditions for existence and uniqueness of a Nash equilibrium for the 2-player case. We analyze two different myopic learning dynamics for the non-equilibrium situations and prove their convergence to Nash equilibrium under mild conditions. For the N-player game between identical players, we characterize all the pure strategy equilibria and identify the worst-case equilibrium, i.e. the equilibrium with maximum total cost. We provide an expression for the measure of inefficiency, similar to the price of anarchy, which is the ratio of the total cost of the worst-case equilibrium to the total cost of the cost minimizing solution and investigate its dependence on different parameters of the game

Calibration of dynamic traffic assignment models with point-to-point traffic surveillance

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2007.Includes bibliographical references (p. 173-180).Accurate calibration of demand and supply simulators within a Dynamic Traffic Assignment (DTA) system is critical for the provision of consistent travel information and efficient traffic management. Emerging traffic surveillance devices such as Automatic Vehicle Identification (AVI) technology provide a rich source of disaggregate traffic data. This thesis presents a methodology for calibration of demand and supply model parameters using travel time measurements obtained from these emerging traffic sensing technologies. The calibration problem has been formulated in two different frameworks, viz. in a state-space framework and in a stochastic optimization framework. Three different algorithms are used for solving the calibration problem, a gradient approximation based path search method (SPSA), a random search meta-heuristic (GA) and a Monte-Carlo simulation based technique (Particle Filter). The methodology is first tested using a small synthetic study network to illustrate its effectiveness. Later the methodology is applied to a real traffic network in the Lower Westchester County region in New York to demonstrate its scalability.(cont.) The estimation results are tested using a calibrated Microscopic Traffic Simulator (MITSIMLab). The results are compared to the base case of calibration using only the conventional point sensor data. The results indicate that the utilization of AVI data significantly improves the calibration accuracy.by Vikrant Vaze.S.M

Modeling Passenger Travel and Delays in the National Air Transportation System

Many of the existing methods for evaluating an airline's on-time performance are based on flight-centric measures of delay. However, recent research has demonstrated that passenger delays depend on many factors in addition to flight delays. For instance, significant passenger delays result from flight cancellations and missed connections, which themselves depend on a significant number of factors. Unfortunately, lack of publicly available passenger travel data has made it difficult for researchers to explore the nature of these relationships. In this paper, we develop methodologies to model historical travel and delays for U.S. domestic passengers. We develop a multinomial logit model for estimating historical passenger travel and extend a previously developed greedy reaccommodation heuristic for estimating the resulting passenger delays. We report and analyze the estimated passenger delays for calendar year 2007, developing insights into factors that affect the performance of the National Air Transportation System in the United States.United States. Federal Aviation Administration. National Center for Excellence for Aviation Operations Researc

Tarmac Delay Policies: A Passenger-Centric Analysis

In this paper, we analyze the effectiveness of the 2010 Tarmac Delay Rule from a passenger - centric point of view. The Tarmac Delay Rule stipulates that aircraft lift-off, or an opportunity for passengers to deplane, must occur no later than three hours after the cabin door closure at the gate of the departure airport; and that an opportunity for passengers to deplane must occur no later than three hours after the touchdown at the arrival airport. The Tarmac Delay Rule aims to protect enplaned passengers on commercial aircraft from excessively long delays on the tarmac upon taxi-out or taxi-in, and monetarily penalizes airlines that violate the stipulated three-hour tarmac time limit. Comparing the actual flight schedule and delay data after the Tarmac Delay Rule was in effect with that before, we find that the Rule has been highly effective in reducing the frequency of occurrence of long tarmac times. However, another significant effect of the rule has been the rise in flight cancellation rates. Cancellations result in passengers requiring rebooking, and often lead to extensive delay in reaching their final destinations. Using an algorithm to estimate passenger delay, we quantify delays to passengers in 2007, before the Tarmac Delay Rule was enacted, and compare these delays to those estimated for hypothetical scenarios with the Tarmac Delay Rule in effect for that same year. Our delay estimates are calculated using U.S. Department of Transportation data from 2007. Through our results and several sensitivity analyses, we show that the overall impact of the current Tarmac Delay Rule is a significant increase in passenger delays, especially for passengers scheduled to travel on the flights which are at risk of long tarmac delays. We evaluate the impacts on passengers of a number of rule variations, including changes to the maximum time on the tarmac, and variations in that maximum by time-of-day. Through extensive scenario analyses, we conclude that a better balance between the conflicting objectives of reducing the frequency of long tarmac times and reducing total passenger delays can be achieved through a modified version of the existing rule. This modified version involves increasing the tarmac time limit to 3.5 hours and only applying the rule to flights with planned departure times before 5pm. Finally, in order to implement the Rule more effectively, we suggest the tarmac time limit to be defined in terms of the time when the aircraft begin returning to the gate instead of being defined in terms of the time when passengers are allowed to deplane.This research was supported by the Federal Aviation Administration National Center of Excellence for Aviation Operations Research (NEXTOR II)

Modeling Airline Frequency Competition for Airport Congestion Mitigation

Demand often exceeds capacity at congested airports. Airline frequency competition is partially responsible for the growing demand for airport resources. We propose a game-theoretic model for airline frequency competition under slot constraints. The model is solved to obtain a Nash equilibrium using a successive optimizations approach, wherein individual optimizations are performed using a dynamic programming-based technique. The model predictions are validated against actual frequency data, with the results indicating a close fit to reality. We use the model to evaluate different strategic slot allocation schemes from the perspectives of the airlines and the passengers. The most significant result of this research shows that a small reduction in the total number of allocated slots translates into a substantial reduction in flight and passenger delays and also a considerable improvement in airlines' profits

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Competition and congestion in the US NAS : multi-agent, multi-stakeholder approaches for evaluation and mitigation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 273-280).The US National Aviation System (NAS) is a complex system with multiple, interacting agents including airlines, passengers, and system operators, each with somewhat different objectives and incentives. These interactions determine the state of the system. NAS congestion and delays result in additional operating costs and reduced profitability for the airlines, a decrease in the level-of-service to passengers, and a decrease in the efficiency of NAS resource utilization. We evaluate the congestion impacts on the NAS stakeholders while explicitly accounting for their interactions and propose congestion mitigation mechanisms that are beneficial to these different stakeholders. We measure the extent to which the NAS capacity is being inefficiently utilized. We show that at the current level of passenger demand, delays are avoidable to a large extent if we control the negative effects of competitive airline scheduling practices, thus providing critical insights into the nature and causes of delays. We develop a detailed framework using data fusion and discrete choice modeling' for generating disaggregate passenger travel data. We characterize the impacts of airline network structures, schedules and operational decisions on passenger delays. We propose a parametric game-theoretic model consistent with the most popular characterization of frequency competition. We prove that the level of congestion in a system of competing airlines is an increasing function of 1) the number of competing airlines, 2) a measure of the gross profit margin, and 3) the frequency sensitivity of passenger demand. We propose a game-theoretic model of frequency competition under slot constraints and provide empirical and algorithmic justifications of the suitability of the Nash equilibrium solution concept for modeling these games. We devise and assess new administrative strategies for congestion mitigation. We show that a small reduction in the total number of allocated slots translates into a substantial reduction in delays, and also a considerable improvement in airlines' profits. We develop an equilibrium model of frequency competition in the presence of delay costs and congestion prices. We find that the success of congestion pricing critically depends on the characteristics of frequency competition in individual markets. We also identify critical differences between flat pricing and marginal cost pricing. Key words: Airline Scheduling, Airline Frequency Competition, National Aviation System, Stakeholders, Multi-agent Models, Nash Equilibrium, Game Theory, Price of Anarchy, Passenger Delays, Cancellations, Missed Connections, Cost of Passenger Disruptions, Administrative Slot Controls, Slot Reduction, Congestion Pricing.by Vikrant Suhas Vaze.Ph.D

Inter-airline Equity in Airport Scheduling Interventions

In the absence of opportunities for capacity expansion or operational enhancements, air traffic congestion mitigation may require scheduling interventions aimed to control the extent of overcapacity scheduling at busy airports. Previous research has shown that large delay reductions could be achieved through comparatively small changes in the schedule of flights. While existing approaches have focused on minimizing the overall impact of scheduling interventions across the airlines, this paper designs, optimizes, and assesses a novel approach for airport scheduling interventions that incorporates inter-airline equity objectives. It relies on a lexicographic modeling architecture based on efficiency (i.e., meeting airline scheduling preferences), equity (i.e., balancing scheduling adjustments fairly among the airlines), and on-time performance (i.e., mitigating airport congestion) objectives, subject to scheduling and network connectivity constraints. Theoretical results show that, under some scheduling conditions, equity and efficiency can be jointly maximized. Computational results suggest that, under a wide range of current and hypothetical scheduling settings, ignoring inter-airline equity can lead to highly inequitable outcomes, but that our modeling approach achieves inter-airline equity at no, or small, losses in efficiency. Keywords: airport demand management, inter-airline equity, efficiency-equity trade-off, integer programming, dynamic programming, queuing mode