AGIFORS Airline
Operations 2003
Technical Program
Presentations
( Based on submitted abstracts to date*
)
Combining event generation and optimization for
comparison of operational performance of schedules
Tomas Larsson - Carmen Systems AB
This presentation shows how operations solvers,
Carmen Fleet Recovery Solver and Carmen Passenger Recovery Solver,
can be used together with a simulation module for event generation
to compare the operational performance of different schedules. The
methods used will be presented together with results from
simulations performed for British Airways.
Decision Support for Hub Reduction
Tim Niznik - American Airlines
We discuss the development and implementation of
an automated tool that identifies alternative cancellation plans to
address operational irregularities such as those caused by
snowstorms, thunderstorms, and ATC ground delays. These plans are
constructed so as to minimize the impact on passengers, crew, and
aircraft routings using an approach that combines subject matter
expertise with mathematical optimization techniques.
Degradable Airline Scheduling Part II
Laura S Kang - MIT Operations Research Center
We present a methodology for deriving airline schedules that are
robust to disruptions cased by bad weather. In this methodology, the
existing schedule is partitioned into independent sub-schedule or
layers -- prioritized on the basis of revenue -- that provide
airlines with a clear delay/cancellation policy and may enable them
to market and sell tickets for flight legs based on passenger
preference for reliability. The problem is modeled as an integer
program. We present various solution approaches and compare
solutions. Results indicate that no additional aircraft are required
to increase the number of itineraries in the protected layers from
891 to 938 and to increase the corresponding revenue in the
protected layers from 60% to 71%.
Dream and Reality - Schedule Punctuality
Control
Cheng-Lung Wu, Department of Aviation - University of New South
Wales
This presentation is to highlight some issues
regarding schedule punctuality control. We will talk about a
stochastic schedule simulation model, which is able to simulate
uncertainties in schedule operations and to generate simulated
schedule punctuality figures. This model, if compared with others,
considers stochastic factors in airline schedule operations, e.g.
reactionary delays and passenger delays, so to bring airline
schedulers a mimic simulation environment to test run draft schedule
plans. The schedule reliability issue will also be covered by
comparing simulation results of the ?dream case? with real-world
operational data from a European airline.
MEANS MIT Extensible Air Network Simulation
John-Paul Clarke - MIT International Center for Air
Transportation
The National Airspace System (NAS) is a complex
adaptive system. Thus, the behavior of the entire system is
difficult to predict, even in instances where there are only a few
agents interacting. MEANS is a modular simulation tool that may be
used by airlines and by air traffic control to predict the behavior
of the NAS even in instances where the behaviour of individual
agents is stochastic.
NZ Express - Opportunities for Operations Research
Amanda Day, Rochelle Meehan - Operations Research Team, Air New
Zealand
On the 1st of November last year Air New Zealand Express Class
hit the domestic skies. This was a strategic decision made by Air
New Zealand to sure up the domestic market. This was one area the
company felt they were vulnerable, particularly to the introduction
of new competitors. Up to this point NZ Express has been a huge
success. With passenger re-education the load factors have increased
and more people than ever are flying domestically in New Zealand.
The purpose of this talk is to identify some of the issues that have
arisen out of this introduction and look at the opportunities that
are available for operations research.
On Time Performance - a Strategic and Operational Imperative
Kathleen Lee, Jeff Moore - Operations Research Team, Air New Zealand
The purpose of this talk is to acknowledge the dynamics of On
Time Performance which have been identified by the Operations
Research Team and the methods which we will use to highlight the key
levers and drivers. Our task is to develop a system which will set
targets for different departments and help them to understand their
impact and contribution to the airline's On Time Performance. We
will also discuss the issues we encountered during our modelling
process.
Robust Flight Scheduling
Lee Loo Hay, Lee Chul Ung and Tan Yen Ping - National University
of Singapore
Traditional methods of developing flight schedules generally do
not take into consideration disruptions that may arise during actual
operations. Potential irregularities in airline operations, such as
equipment failure and baggage delay are not adequately considered
during the planning stage of a flight schedule. As such, flight
schedules cannot be fulfilled as planned and their performance is
compromised, which may lead to huge losses in revenue for airlines.
In this paper, we develop a model that improves the robustness of a
given set of flight schedules. A simulation model, SimAir, has been
employed to evaluate the performance of the flight schedule. A
multi-objective genetic algorithm (MOGA) procedure has been
developed to improve the robustness of the flight schedule while
preserving the original aircraft rotations and crew rosters. It
considers different performance measures such as flight
cancellation, operational cost and other performance indices as
well.
Robustness Issues in Pairings Optimization
David M Ryan - University of Auckland
Besides constructing aircrew Pairings with minimal
cost, airlines also wish to construct pairings which are robust in
the sense that flight schedule disruptions are less likely to
propagate delays into the future. In general a minimal cost solution
is likely to lack robustness and conversely a solution with maximum
robustness (however this is to be measured) is likely to be more
expensive. A measure of robustness for each pairing will be
developed and the concept of a robustness objective will be
discussed. The two objectives of cost and robustness will be treated
in a bicriteria optimisation to generate "efficient"
pairings which do not allow a simultaneous improvement in cost and
robustness.
A Robust Optimization
Approach for Aircraft Schedule Dependability: Simulation, Evaluation
and Re-flow
Qing
Zhao, et. al.
- Operations Research Department, Delta Technology
To build a dependable
aircraft schedule is a very challenging and significantly important
task since many other airline decisions such as crew and maintenance
scheduling are based heavily on it. In this talk we will present a
robust optimization approach to build a dependable aircraft
schedule. In the approach, we will describe a simulation process
used to identify problem flight legs which cause flight delays and
cancellations. We then describe a two-step method to improve the
dependability of an aircraft schedule by localizing and minimizing
the damaging effect of those problem flight legs.
SIMMAIR - Status Report
Ellis Johnson - Georgia Institute of Technology ISYE
SIMAIR is a research tool for studying appropriate
recovery methods from a disruption to an airline’s schedule. This
presentation will describe SIMAIR in terms of its objectives,
functions and purposes. We will describe its modular structure.
Then, we will discuss the current status of SIMAIR including a
demonstration of the use of its major modules, Simulation,
Controller, and Recovery. Next, we will discuss the kinds of
decisions that can be made with SIMAIR. Lastly, we will discuss the
outputs that are collected.
Virtual Hubs - A Case Study
Michelle Karow - MIT International Center for Air Transportation
Inclement weather at an airline hub airport
generates a schedule recovery problem of reallocating flights in
real-time. By shifting connecting banks to strategically located,
under-utilized airports during these irregular operations, the
airline can reduce costs and aircraft delays relative to current
industry rescheduling practices. These proposed virtual hubs will
host select connecting traffic shifted from the original hub with
the objective of minimizing system passenger delays. A linear
program is used to allocate connecting flights and their
corresponding passengers to either hub over time windows spanning
the period of irregularity subject to the available capacity at the
original and virtual hub airports. In addition to the methodology, a
case study will be presented from a major US carrier.
Panel Discussions
User Interface Design, Development, and Experience
Panelists
- John-Paul Clarke, MIT
- Peter Geard, Air New Zealand
- Ladislav Lettovsky, Sabre Inc. (moderator)
Effective Implementation of Decision Support
Tools
Panelists
- Michael Clarke, Sabre Inc. (moderator)
- Tim Niznik, American Airlines
- Ian Russel, Air New Zealand
Vendor Presentations
Ad Opt Technologies
Carmen Systems AB
Preston Aviation Solutions
Sabre Airline Solutions
SBS International
* Technical
Program is subject to change
Call for papers
Come and share with us your ideas,
thoughts, current trends, philosophies, and latest technological
advances on topics ranging from airport security, airport systems,
ground resource management, maintenance, tactical planning, and
operations control.
If you are interested in presenting at the study
group meeting, please complete the on-line
registration form and submit it directly via the
www. As always, talks are
subject to approval, and time slots are available on a first come,
first serve basis - so if you are interested, act now!
The AGIFORS
Airline Operations 2003 conference technical program is currently
being put together, for more information please contact tim.niznik@aa.com.
Please refer to previous
years conference proceedings for a complete listing of technical talks
given in the past at AGIFORS Airline Operations
meetings.
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