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AGIFORS Annual Symposium 2006 |
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Technical Program ( Based on submitted abstracts to date* )Monday - 02 October 2006 Continuous Descent Arrivals: Flight
Procedures that Provides Significant Fuel Savings There is a pressing need, given the rising cost of fuel, for operational procedures that reduce fuel burn. One very promising procedure, the Continuous Descent Arrival (CDA) where aircraft remain at cruise altitude for as long as possible before landing, has thus far been limited to low-traffic situations. We present an overview of the procedure, results of simulator and flight test experiments showing that airlines can save up to 364 pounds of fuel per arrival, and details of the OR approach used to optimize the procedure for the high-traffic situation at Los Angeles International Airport (LAX).
Light Maintenance Assignment Results in a Real World In 2001 Alitalia started with a big project with the goal to reanalyse and redefine all the processes related to light maintenance and to develop a web application to full manage it. This project involved OR Alitalia department with the development of an automatic Scheduling and Assignment module. Now that the whole application is going to be delivered we present an overview of the results reached. Maintenance OR Applications at
American Airlines American Airlines is making a concerted effort to provide competitive services for aircraft maintenance. They have a stated goal of obtaining $500 million in 3rd party work. In order to ensure this is a viable and profitable business venture, AA’s OR group has been developing tools and working on the development of decision support systems to optimize and analyze our maintenance processes. This talk will provide an overview of a number of AA initiatives associated with field and shop maintenance activities. In addition it will include a strong pitch to AGIFORS attendees to look at the interesting problem set in this area of the business. Building Optimization Applications
using ILOG ODMS This presentation will give you an insight into recent ILOG optimization developments and will introduce new ILOG Optimization Decision Management System (ILOG ODMS) – a new generation of integrated tools and engines for optimization modeling and application development. CPLEX features high-performance, robust solvers that are widely used within airlines applications such as crew scheduling, fleet scheduling and yield management. ILOG ODMS developments are driven by the need to accomplish key business objectives and rapidly deploy the right flexible solutions. A demo will be presented highlighting the productivity and ease-of-use of ILOG ODMS in terms of model development, debugging and tuning using ILOG OPL Development Studio and the seamless integration with ILOG ODM (Optimization Decision Manager) to rapidly build complete interactive CPLEX-based planning and scheduling applications. Tuesday - 03 October 2006 Robust Scheduling Robust scheduling is an important area in airline OR because increased passenger and cargo demand has not been met by increased airport and airspace capacity, resulting in significant and costly delays and disruptions. We present several ideas for improving the robustness of airline schedules and quantify their potential benefits through analysis and simulation. Ideas include: aircraft routings where ground times are proportional to expected upstream delay; flight departure times that factor in expected upstream delays of aircraft, crew and passengers; independent layering of schedules to prevent delay propagation and provide guaranteed, high-reliability service for a "desired" subset of the itineraries. Flight Scheduling at KLM To get more insight in the robustness of a new flight schedule we have developed a simulation model called Operations Performance Model (OPiuM). This is done with help of state of the art techniques developed by the Technical University of Delft. Not only the activities of the KLM fleet are simulated, also the measures taken by the front office in case of delays are taken into account in OPiuM. We expect that using OPiuM will substantially reduce the operational costs of KLM; changes in the new flight schedule to improve its performance can now be made beforehand. Implementing an En-Route
Optimization Tool at Delta Airlines The Attila™ System, developed by the ATH Group, Inc. (ATH) is primarily an en route aircraft metering tool that optimizes on-time performance and fuel burn by sending guidance messages to the Delta aircraft to adjust speed accordingly. Attila uses a computer-based decision process to optimize aircraft traffic flows in real-time. The system analyses the real-time factors affecting the arrival flow, and calculates optimal arrival times for each aircraft. Once a solution has been determined, Attila automatically generates an ACARS message advising of the corner post (arrival fix) time to each pilot in the arrival flow. Subsequently, Attila continuously monitors the arrival flow and adjusts accordingly. The presentation will describe the Attila system, its OR methods, and how it was implemented at Delta Airlines. The Impact of the Internet on
Airline Fares The author, a 25-year airline executive, will describe the design and early findings of his doctoral research on the topic. The paper won Best Presentation at the Pricing/RM Study Group. Helping Travelocity Transition to
Travel Retailer With approximately $80 billion of travel products sold worldwide in 2005, Sabre is the world’s largest travel distribution system, connecting consumers, travel agents and travel suppliers (airlines, hotels, etc.). In 1996 Sabre launched Travelocity, an online travel company that leverages Sabre’s travel experience and technology to begin selling travel directly to consumers. The foundation of Travelocity’s original business model depended on earning commissions from selling airline tickets and generating revenues from selling advertising space. Travelocity initially took the lead in Internet airline ticket sales, but as new competitors entered the space, Travelocity’s share of travel bookings steadily eroded. In order to survive in this new environment, Travelocity had to become a sophisticated retailer by negotiating marketing agreements with suppliers, managing access to content, and expanding into more profitable lines of business and thus avoid the death suffered by many Internet companies of the period. In May 2002, then-president of Travelocity, Sam Gilliland, asked the Sabre Research Group to help Travelocity adapt to this evolving, new environment and to increase their sophistication as retailers. The Sabre-Travelocity team developed the Enterprise Network Model (ENM) to improve decision-making in this environment. Since 2002, the ENM has yielded over $54 million of incremental value, with a current annual run-rate of $43 million. In this presentation, we’ll describe our experience helping to transform Travelocity from an Internet company surviving on growth to a sophisticated on-line retailer. We’ll address the following topics: 1) customer data and modeling; 2) supply modeling; 3) marketing modeling; 4) modeling to support retail pricing and Low Fare Search (LFS). Finally we summarize the benefits of the ENM to Travelocity and review the transferability of these concepts and models to other applications. Inter-temporal Valuations, Product
Design and Revenue Management We study booking processes over finite horizons that culminate with the delivery of a good or service. We develop an inter-temporal choice model where the consumers choose the product they purchase among the current and the future alternatives taking into account the evolution of their valuations over time. We show that for all capacity levels likely to arise in practice, selling call options on capacity results in significantly higher expected revenues than low-to-high pricing. We analyze a two-period fluid model in detail, and obtain structural results on the optimal revenue function, closed-form distribution-free bounds on the option price and the optimal revenue. Moreover, we show that using options improve the social benefits over low-to-high pricing. Next, we show that the solution to the fluid model is asymptotically optimal heuristic for the stochastic model and extend the model to multiple periods and study the optimal time to issue and exercise call options.
Understanding Seasonality Analyzing Booking Data Understanding Seasonality means to find patterns which occur at given times of the year; it’s a basic component in a demand forecast model. In this study we analyze booking data for every flight day to find the demand behavior. Our strategy is to choose variables that better explain the demand according to quantity and quality and then use a cluster analysis to classify the heterogeneous behavior of flights. The aim is to give a “seasonality label” to every flight in order to adjust demand forecasting that can direct revenue and price policies. The presentation will give an overview of the problem and of clustering methods chosen for our goals. Building Optimization Based Airline
Solutions in XpressMP Mathematical Programming based optimization techniques have traditionally been used in the airline industry for variety of problems such as crew scheduling, pairing, aircraft routing, etc. In this talk we describe how Dash Optimization's tools can also be used to build solutions using novel approaches such as robust optimization under demand uncertainty. We show how Xpress tools can be quickly configured to address range of problems: from those occurring in Yield Management to the ones in Airport Operations Management. Thursday - 05 October 2006 Dynamic Airline Scheduling:
Models, Algorithms and Experiments Demand stochasticity is a major challenge for the airlines in their quest to produce profit maximizing schedules. Even with an optimized schedule, many flights have empty seats at departure, while others suffer a lack of seats to accommodate passengers who desire to travel. Recognizing that demand forecast quality for a particular departure date improves as the date appraoches, we tackle this challenge by developing a dynamic scheduling approach that re-optimizes elements of the flight schedule during the passenger booking period. The goal is to match capacity to demand, given the many operational constraints that restrict possible assignments. We introduce flight re-timing as a dynamic scheduling mechanism and develop a re-optimization model that combines both flight re-timing and flight re-fleeting. Our re-optimization approach, re-designing the flight schedule at regular intervals, utilizes information from both revealed booking data and improved forecasts available at later re-optimizations. Experiments are conducted using data from a major U.S. airline. We demonstrate that significant potential profitability improvements are achievable using this approach. Multi Flight Demand Untruncation
with Recapture A new method for revenue management demand untruncation using origin-destination booking activity across multiple flights in a market will be discussed. The new approach involves choice models which estimate market-class group demand across flights. Closed-form solutions for estimating flight spill and recapture will be presented. These estimates are unique to the specific pattern of flight closures and bookings occurring during the departure date and reading day considered. By estimating and correcting for recapture effects, the traditional problem of “double counted” demands (i.e. spilled demand on closed itineraries and recaptured traffic on open itineraries are both included) is avoided. The resulting “first-choice demand” estimates should provide a more stable underlying time-series for future demand forecasting. Initial computational experience applying the new methodology indicates considerable promise in reducing demand forecast errors. Applications of Discrete Choice
Models to Airline Passenger Behavior In recent years, discrete choice models have been used to model airline customer behavior. This presentation reviews successful applications of discrete choice models in the airline industry, with a particular focus on scheduling models. An emphasis is placed on clarifying concepts such as “nested logit models” and “schedule delay function” that have been mis-interpreted in the airline literature. Quantifying the Risks Associated
with Market Performance This paper presents a nonlinear extension to the First-Order Second-Moment probabilistic approach for quantifying likely market performance. This approach uses basic concepts of engineering reliability and risk to estimate the probability that revenue performance of a service exceeds costs. This methodology also provides a mechanism for quickly evaluating performance requirements in terms of revenues or costs for a desired risk level. Extending this methodology to nonlinear performance functions allows quantification of risk associated with attributes like the interaction between passenger fares and demands as a function of elasticity and the incorporation fuel costs. Using this approach, decision makers can evaluate the risks associated with new initiatives such as new pricing structure or a fuel hedging plan. Reducing Costs with Connecting Flow
Management for Ground Operations For major airlines, missed connections for passengers or luggage on hubs can result into significant additional costs. It is therefore a concern for ground operations department to manage the risk of misconnections throughout planning processes, from seasonal sizing to D-1 scheduling. This can be efficiently supported by OR tools when they are adapted or developed to handle this objective, flow forecasts have to be provided, optimization has to deal with a new complexity. AF OR department has been closely involved into such improvements on application for luggage handling and parking point assignment. Efficient Turnaround Communications An efficient aircraft turnaround process is critical success factor in an airline’s operation. Air-craft turnaround processes encompass passenger processing, baggage unloading/loading, catering, etc. But are these processes currently coordinated in a truly efficient manner? What if a new communications platform was established from the ground up to make turn-around processes truly efficient? This presentation will show the critical importance of communication in turnaround processes and introduce a means for creating a new communications framework to increase turnaround efficiency.
SCAI: A Seasonality System Integrated with Airmax Seasonality analysis is the first step in a Revenue Management (RM) system: its goal is to analyze historical data according to user needs and classifying them for improving RM forecasting systems. SCAI (Seasonality Cluster Analysis and Indexes) is a software system developed by Alitalia Servizi for covering the process of seasonality understanding. Through the implementation of indexes and measures, it gives the possibility to cluster better historical data either using mathematical formula or user feeling data. SCAI is also designed for exporting information towards forecasting systems running in Airmax (Sabre software systems). Optimization algorithms implemented
in APM software APM Technologies SA is based in Geneva, Switzerland, and produces modular management software for airlines. APM products provide informed, intelligent solutions to problems related to aircraft scheduling, aircraft operations, aircraft maintenance, crew pairing, crew roster, disruption recovery and financial profitability. This talk reviews the optimization methods adopted by APM and describes the details of the minimization algorithms implemented in the various applications. Friday - 06 October 2006 A Disruptions Based Approach for
Sizing Cabin Crew Stand by Blocks Day of operations crew disruptions can be evaluated and anticipated by a statistical approach. Disease, unassigned tasks and scheduled flights are contributing to these disruptions. A new model has been developed to create and plan stand-by blocks in order to insure a correct level of reserve on each day. The target is to minimize the number of stand-by blocks such that the maximum crew disruptions are managed, taking uncertainty into account. The Analytics of Preferential
Bidding Lifestyles are as individual, as the people who live them. Preferential Bidding follows this general trend of supporting individuality by taking personal preferences of crewmembers into account when building monthly schedules. In an environment where seniority of crew needs to be factored into the process, preferential bidding systems often still rely on rather simplistic solution methods. In this presentation we will describe advanced analytical methods that maximize crew satisfaction while respecting operational constraints, provide transparency of the award, and allow crewmembers to understand why bids have and have not been granted. Operations Research methods in general, and optimization algorithms in particular prove very powerful in solving preferential bidding problems. We will give concrete examples from our own experience of applying such methods. Optimised Catering Supply
Chain Management Supply Chain Management is constantly mentioned as a key issue for many types of compa-nies, including airlines. But, what about the Catering Supply Chain? What are the key issues and problems in managing an airline’s catering supply chain? What are the key issues and challenges within the catering supply chain? This presentation will answer these questions as well as introduce a means a means for optimising the catering supply chain. The Future of
Network Based Modeling and Forecasting in the Transportation Poor data availability and complexity of transportation networks are common obstacles to creating detailed network simulation models for the air freight industry. We will demonstrate the development of such a model with the aid of sophisticated algorithms and highly skilled analysts with access to a variety of data sources. Our model incorporates network generation based on airline schedules, demand distribution based on data synthesis and optimization, and a demand and network growth forecasting engine. We will demonstrate how the model has aided our clients in making important strategic decisions and discuss extensions to sea freight and other industries. Call for papersThe 46th Annual Symposium of the Airline Group of the International Federation of Operational Research Societies (AGIFORS) features a comprehensive program covering the whole spectrum of airline operations research. This year’s symposium will be held from 01 – 06 October 2006 in Rome, Italy. Contributions to the technical program are solicited in the following areas, but are not limited to, flight scheduling, pricing, yield management, maintenance and engineering, crew, ground resources, and finance. Papers covered by active Study Groups, as well as other topics not covered by active Study Groups, are sought. Airline, consultant, academic, and industrial research representatives are all encouraged to attend. Presentations are 30-35 minutes, with 10-15 minutes for Q&A. Symposium proceedings will be published by January 2007. Deadlines and Requirements Abstract Submissions - August 15, 2006 Please send all submissions via the online form. Submit abstracts online (maximum 100 words). Include a title and identify the corresponding author. For each co-author, include full name, affiliation, complete address, telephone number, FAX number, and electronic mail address or URL. Paper/Presentation Submissions - September 15, 2006 Corresponding author provides both an electronic file submission of the presentation/paper for inclusion on the CD-version of the Proceedings and a photo-ready copy for the printed Proceedings. Please note the following conditions for inclusion of your paper in AGIFORS 2006:
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