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Scheduling and Strategic Planning Annual Conference 2018
  • A forum for airline managers and personnel, vendors, and members of academia to discuss trending issues facing airline scheduling and planning, offer potential solutions, and provide opportunity for networking
  • Airline updates on the latest plans, challenges, and models and systems needs 
  • Fifteen (15) technical presentations from leading experts in the airline industry
  • Airline representatives from Aeroflot, Air France - KLM, American Airlines, British Airways, Copa Airlines, Hawaiian Airlines, LATAM, Siberian Airlines, United Airlines
  • Academic/Industry representatives from Boeing, Dartmouth College and Carnegie Mellon University, Embry Riddle Aeronautical University, German Aerospace Center (DLR)

  • Vendors exhibition including AD OPT (Kronos), Amadeus, Boeing, FICO, FlightAware, Flight Global / DiiO, GE Aviation Digital, Global Eagle Entertainment, IBS Software Services, INFORM GmbH, Jeppesen Sanderson, Lufthansa Consulting, Lufthansa Systems, M2P Consulting, OpsGenie, Optym, PASSUR Aerospace, Predictive Mobility, Robust Analytics, Rockwell Collins, Sabre Airline Solutions, SITA, The Weather Company, TR2L and the Boston Consulting Group

For questions or more information, please contact:

- Cumhur Gelogullari - cumhur.gelogullari@aa.com (co-chair)

- Lisa Noell - lisa.m.noell@boeing.com (co-chair)

- Derek Sutton – derek.sutton@hawaiianair.com (host rep)


The registration fee includes conference technical materials, all scheduled meals and social events outlined in the meeting agenda. Registration fee is 300USD per airline/academic delegate, 600USD per industry delegate, and 900USD per vendor delegate. 


Register Now

Late Registrations

Registrations received after May 1st 2018 will be considered late and will incur an additional 100USD late fee, with no exceptions.   

Cancellation Policy

Any cancellation requests before May 1st 2018 will be subject to a 100USD service fee per person, after this date the cancellation fee will be 150USD per person to cover the incurred expenses.

Call For Presentations

You are invited to submit a proposal to present at the meeting. Come and share with us your ideas, thoughts, practical innovations, current trends, case studies, philosophies, and latest advances on the topics which are relevant to you. 


Abstract Submission

For abstract submission, please use the form above.

If you cannot access the form, please send the title and the abstract of your presentation to  cumhur.gelogullari@aa.com

Abstract Submission Deadline: April 30th

Draft Presentation Due: May 5th

Final Presentation Due: May 10th


  • A 30-45 minute presentation
  • Willingness to comply with requests for additional information and clarification on abstract and/or presentation material
  • Willingness to tailor a presentation for the AGIFORS SSP audience and to accept direction from the selection committee in doing this
  • Must register and attend the meeting

General Information


Business Events - Business Casual

Welcome Reception - Business Casual

Social Events - Evening Casual



Honolulu weather in May would be good. Plan for low 70F/20C and high 85F/30C with a small chance of rain.


Waikiki Beach Marriott Resort & Spa

Official conference hotel is Waikiki Beach Marriott Resort, located next to Diamond Head Crater and Waikiki Aquarium, and is close to Pearl Harbor.

Adress: 2552 Kalakaua Ave

Honolulu, Hawaii, USA, 96815

Tel: +1 808-922-6611

Fax: +1 808-921-5255

Update: Conference hotel is sold out

A limited number of rooms have been blocked at the Marriott Waikiki Beach Resort for the conference.  Reservations must be made via our dedicated website by 15 April 2018 to receive the specially negotiated rate of 160 USD for single/double occupancy (inclusive wifi access, exclusive of service fees and taxes).  A discounted resort fee of 15 USD (vs 37 USD) will be applied at check-in.  All credit card information must be provided to confirm reservations using the customized link below.

Book the Hotel

Host Airline

Tentative Agenda

Program is tentative and is subject to change without notice



Monday, 21 May



Welcome Reception and Cocktails
Marriott Waikiki Beach Resort


Tuesday, 22 May

08:0015:00 Conference Registration
08:00 08:30 Conference Opening
08:30 09:30 Keynote Address 
09:30 10:00 Coffee Break
Business Lunch
13:00 14:30 Presentations
14:3015:00 Coffee Break
15:00 18:00 Vendor Updates/Exhibition


Networking Dinner
Marriott Waikiki Beach Resort


Wednesday, 23-May

08:30 10:00 Joint Technical Session SSP / Airline Ops
10:0010:30Coffee Break 
10:3012:00Joint Technical Session SSP / Airline Ops
Business Lunch
14:30 15:30 Vendor Updates/Exhibition
15:3016:00 Coffee Break 


Chief Luau Paradise Experience
Thursday, 24-May
10:0010:30Coffee Break
10:30 12:00Presentations
12:0013:00Business Lunch
14:3015:00Coffee Break
15:0016:00Award Ceremony / Conference Close
Program is tentative and may change without notice

Conference Sponsors

If your company is interested in sponsorship opportunities, we are offering a variety of sponsorship packages for your consideration.  With each package, your company with be recognized an official sponsor for the conference, and recognized at the start of each day’s proceedings.  In addition, you will receive additional benefits based on your level of sponsorship.

Bronze – Placement of company signage at the conference registration desk, and backdrop of podium (1000 USD)

Silver – Acknowledgement at a select social event, preferential selection of booth location, plus benefits of the bronze level (2000 USD)

Gold – Complimentary upgrade to an executive level club suite, plus benefits of the silver level (4000 USD)

If you would like to sign up for one of the limited sponsorship opportunities, please complete the online submission form at your earliest convenience. Please add in the comments section "Sponsorship for SSP 2018". 

Visa Information

The United States requires visas or electronic authorization for travel from most countries. You can obtain more information at https://travel.state.gov/content/visas/en.html


If you need a visa, please check the wait times at your consulate and allow for plenty of time. If you need supporting documentation, please contact the conference chairs.

Social Activities

Welcome Reception

Monday, May 21, 2018, 19:00 to 21:00

Pualeilani Terrace

Marriott Waikiki Beach Resort

Join us at the Marriott Waikiki Beach Resort where you can gather to relax, network with other conference delegates. Enjoy views of the surrounding area while savoring a sumptuous selection of international treats and drinks. It will be an ideal time to re-kindle old friendships, and meet and great arriving conference delegates before the official start of the technical program, and vendor exhibition.


Networking Dinner

Tuesday, May 22, 2018, 20:00 to 22:00

Experience a wonderful evening on the Pualeilani Terrace, conveniently located at the Marriott Waikiki Beach Resort.  Enjoy an award winning dining experience in the comfort of the conference hotel.  Relax and unwind with fellow delegates in preparation for the second day of the technical program.


Wednesday, May 23, 2018, 16:00 to 19:30

Enjoy this exciting excursion to the award winning Chief’s Luau where we will join Chief Sielu Avea and his ohana (family) for an amazing evening of Polynesian culture and fun.  You will have an opportunity to immerse yourself in the rich heritage of the Islands. Sip a Mai Tai cocktail and sink your teeth into a lavish Hawaiian feast, a sumptuous blend of traditional luau foods blended with Hawaiian regional cuisine. And finally, enjoy a thrilling Polynesian show.

Conference Schedule

Monday 21 May 2018

19:00 - 21:00 Welcome Reception and Cocktails

Tuesday 22 May 2018

07:00 - 08:00 Breakfast Buffet (Salon C)

08:00 - 08:30 Introductions / Conference Overview

08:30 - 09:30 Keynote Address
Jeff Helfrick

Vice President – Airport Operations

Hawaiian Airlines

09:30 - 10:00 Coffee Break (Salon B)

10:00 - 10:30

Current Market Outlook

Matthew Kosmal


10:30 - 11:15

An Innovative and Efficient Solution Methodology to Integrated Fleet Assignment Problem

Shahram Shahinpour (speaker), Xiaoqing Sun, Sergey Shebalov

Sabre Inc.

11:15 - 12:00 Airline Updates - Aeroflot, Air France - KLM, American Airlines

12:00 - 13:00 Business Lunch (Salon C)

13:00 - 13:45

Models to Support Scheduling Decisions in a Complex Network: Fleet Assignment Model as an Example

Yuxi Xiao (speaker), Ronald Chu, Luis Ochoa

American Airlines

13:45 - 14:30 Airline Updates - British Airways, Copa Airlines, LATAM Airlines

14:30 - 15:00 Coffee Break (Salon B)

15:00 - 18:00 Vendor Presentations / Exhibition

 Global Eagle

 Lufthansa Systems

 IBS Software Services

 Sabre Airline Solutions






 GE Aviation Digital





 Predictive Mobility

20:00 - 22:00 Dinner at The Pualeilani Terrace (Marriott)

Wednesday 23 May 2018
07:00 - 08:30
Breakfast Buffet (Salon C)

08:30 - 09:00  
Misconnect Passenger Analysis using a Visual Platform

Brett Bonner

United Airlines

09:00 - 09:30   Human Plus Artificial Intelligence for Robust Block Time Forecasting

Ece Ay


09:30 - 10:00   Leveraging Data Science to Find Punctuality Quick Wins

Blaise-Raphael Brigaud & Solene Richard

Air France - KLM

10:00 - 10:30   Coffee Break (Salon B)

10:30 - 11:00   Resilient Airline Scheduling - Optimize On-Time Performance Based on Delay Risk Prediction

Judith Semar & Marius Radde

Lufthansa Systems

11:00 - 11:30   Improving On-Time Performance through Robust Routing

Nabin Kafle

JetBlue Airways

11:30 - 12:00   Robust Airline Scheduling with Optimal Block and Ground Times

Pranav Gupta


12:00 - 13:15   Business Lunch (Salon C)

13:15 - 14:00

Forecasting passengers using designer machine learning

Jan van der Vegt

Air France - KLM

14:00 - 14:30  

Market Demand Stimulation

Lisa Noell


14:30 - 15:30   Vendor Presentations / Exhibition


 M2P Consulting

 Flight Global

 PASSUR Aerospace

 ATAC Corporation


15:30 - 16:30   Coffee Break (Salon B)

16:00 - 19:30 Chief's Luau Paradise Experience

Thursday 24 May 2018

07:00 - 08:30 Breakfast Buffet (Salon C)

09:00 - 09:30

Network Dependency Ratio

Alexandre Pizzut, Valentina Crippa

Air France - KLM

09:30 - 10:00 Airline Updates - Hawaiian Airlines, United Airlines

10:00- 10:30 Coffee Break (Salon B)

10:30 - 11:15

Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice

Vikrant Vaze (speaker), Keji Wei,  Alexandre Jacquillat

Dartmouth College, Carnegie Mellon University

11:15 - 12:00

Regulation of Frequent Flyer Programs on an International Scale: A Pilot Study for Turkish Airlines

Bora S. Unsal

Embry Riddle Aeronautical University

12:00 - 13:00
Business Lunch (Salon C)

13:00 - 13:45

Balancing Commercial and Operational KPIs in Aircraft Routing for GOL

Tomas Larsson


13:45 - 14:15 New Market Ramp Up
Cumhur Gelogullari
American Airlines

14:15 - 14:45 Coffee Break (Salon B)

14:45 - 15:30 Award Ceremony / Conference Close

Program subject to change without notice

Technical Program

Current Market Outlook


Boeing continues to look to the future with our Current Market Outlook (CMO) publication, which is Boeing’s long-term forecast of passenger and cargo traffic and the number of airplanes necessary to support that expected demand. Our Current Market Outlook is one of the longest-published forecasts in the aviation industry and has proven to be among the most accurate.  As the global economy and markets evolve, so must the focus of our industry forecasts. In 2017, Boeing expanded the CMO to include all of the services required to support the operation of commercial aviation products around the world. The outlook for the commercial support and services market is covered in depth in Boeing’s new Services Market Outlook (SMO). Both the CMO and SMO provide key forecast metrics as well as insights and supporting analysis. This presentation will review Boeing’s latest CMO and SMO forecasts and Boeing’s view of the current market environment and future of aviation and the importance of aviation services to the industry.

An Innovative and Efficient Solution Methodology to Integrated Fleet Assignment Problem

Sabre Inc.

Fleet assignment deals with assigning an equipment type to a leg to best match seat capacity with passenger demand and maximize profit. Two steps are involved. Demands are generated by airline's forecasting system based on an input schedule and are fed to Fleet Assignment Model (FAM) which changes the assignment on a leg or cancels a leg. The benefit to integrate the two systems is significant. Canceling or reducing capacity of a leg can have significant impact on other legs. Models that consider origin and destination effect and integrate other aspects of demand forecasting systems have been proven to be very hard to solve. In this presentation we explore the root cause of intractability of such problems and propose an efficient solution methodology to integrated FAM. Proposed method has been tested on O&D FAM and improvement compared to leg FAM is significant. This methodology provides a framework to fully integrate airline forecasting system and FAMs.

Models to Support Scheduling Decisions in a Complex Network: Fleet Assignment Model as an Example

American Airlines

After a merger with US Airways in 2013,  the new American Airlines, operating in 9 hubs and flying to 350 destinations in 50 countries, became the largest airline in the world by its fleet size and passenger carried. In the presentation, we discuss a set of new challenges to effective scheduling brought about by the broad scale of the combined network. One major challenge is to solve a big network problem efficiently given a set of complex constraints. Another important one is to build practical models that streamline and automate manual business processes, while fully integrating into the schedule generation process. It is essential to understand the difference between optimality of the model solution and effectiveness of the results from the business standpoint (“acceptable optimality”).  A certain level of gap to optimality is imperative for obtaining quick turnaround with a big problem.  

Forecasting passengers using designer machine learning

Air France - KLM

Predictions for the number of airline passengers that will board a particular flight have a variety of uses, including revenue management, fuel planning, the anticipation of no-shows or excess hand luggage, and catering supply chain management. In this talk, we outline the business requirements for a passenger forecast system, formalize the machine learning problem at hand, discuss ways to evaluate model candidates, and subsequently advance through a series of tailor-made algorithms with increasing complexity. From shortcomings of each model candidate, we introduce a new modular improvement to the algorithm, moving from a simple linear model to more sophisticated deep learning neural network architectures. We intersperse conceptual model design with snippets of Python code to provide practical handles. In conclusion, we briefly delineate some open modeling challenges associated with this use case.

Market Demand Stimulation


Airlines evaluate existing networks and the demand across O&D markets unserved by a non-stop route to seek out new markets to serve.  When a new nonstop service is added, airlines assume capture of a certain percentage of the existing O&D demand.  Solely accounting for existing O&D demand underestimates the true demand an airline will realize.  New markets stimulate additional demand (e.g., BA’s AUS-LHR route commencing March 2014).  When helping an airline evaluate new markets, Boeing has a specific approach to estimate new market demand stimulation.  We will review Boeing’s approach and a few examples of new market demand stimulation.

Network Dependency Ratio

Air France - KLM

For airlines based on a hub system, the different routes of the network feed each other to generate connecting traffic flows. In Air France, the medium haul network has the key role to feed the long haul one. LH revenues from MH connections are very significant; therefore, they should be reflected in MH performances.

A model to compute the NDR (Network Dependency Ratio) value was created to achieve that. When a MH route is cut, some seats on LH flights will be vacated and generate available capacity to capture the LH demand that used to be spilled (from other connections LH-LH or LH-MH or Local LH). The idea of the NDR is to compute the ratio of the non-recapturable part of revenue and passengers with respect to the expected loss without recapture when a MH route or a MH flight gets cut. NDR can help ranking all MH routes and flights to understand to what extent the whole network depends on them.

Regulation of Frequent Flyer Programs on an International Scale: A Pilot Study for Turkish Airlines

Embry Riddle Aeronautical University

Airline alliances work perfectly for paid flight segments, but there are difficulties for passengers who want to redeem flight miles. Airlines mostly decline requests for award mile seats, not only from their partner airline’s customers but also from their own customers. To overcome the problems associated with redeeming award seats on flights requires a global regulation of the system. In this pilot study, we propose a new quantitative approach, Frequent Flyer Money Saver (FFMS) analysis, that can be used to identify obstacles to redeeming award seats for Turkish Airlines. After obtaining  the study results , the FFMS analysis will be used for to find the optimum system that has the best FFMS ratio for all flag carrier aviation companies under airline alliances. Then I will propose standardizing global frequent flyer redemption system regarding to the properties of this airline. Because of this the business volume of aviation-related industries might increase.

Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice

Dartmouth College, Carnegie Mellon University

We present an original integrated optimization approach to comprehensive timetabling and fleet assignment. Passenger choice is captured by a linearized version of a multinomial logit model integrated into our modeling framework. The resulting model, despite being a mixed-integer linear (rather than a nonlinear) optimization model, is still highly intractable by commercial solvers due to its extremely large size. We develop an original set of multi-phase solution approaches to optimize the network-wide timetable of a major airline carrier within a realistic computational budget. From a practical standpoint, our framework provides decision-support for airlines interested in generating their timetables from scratch, evaluating or enhancing their existing timetables, or analyzing various business strategies such as contemplating or executing mergers and acquisitions, etc. Furthermore, we demonstrate the value of integrating timetabling decisions with other important planning steps, such as frequency planning, to improve the overall profitability of the airline. 

Balancing Commercial and Operational KPIs in Aircraft Routing for GOL


Most airlines use standard flight scheduling products to generate aircraft routings, also for the monthly planning. At Jeppesen, we regard aircraft routing as a process of its own. The standard process of treating aircraft routing as a special case of the scheduling process, and applying the same tools as used for the long-term planning leads to that opportunities for bot increased revenue and improved operational performance are overlooked. Jeppesen has worked together with GOL to use a dedicated aircraft routing optimizer to optimize its operation. The results show both increased sat capacity in key markets and improved operational performance. This presentation describes the process together with results from GOL.

New Market Ramp Up

American Airlines

When a carrier introduces a new nonstop service, especially an international market; it is often believed that it will take some time for the new service to achieve its full revenue potential, as public awareness will increase over time through advertisements, and relationships with travel agents may take time to mature. The ramp up effect is considered in many analyses including revenue performance estimates and new market selection studies, but has been mostly a subjective, based on anecdotal evidence. Our study is an attempt to construct an objective, data driven model for the ramp up effect.

Joint Session, SSP and Airline Ops - Wednesday, May 23rd:

Resilient Airline Scheduling and Operations - Optimizing on-time performance based on delay risk prediction

Lufthansa Systems

Flight schedules regularly get disrupted on the day of operations by events that were unforeseeable at the time when the schedule was built. While this can hardly be avoided, we aim to minimize delay risks on a standard day of operations. Delays caused by special events or irregularities (e.g. major technical defects, thunderstorms) cannot be taken into account by scheduling, they have to be addressed in a later process phase by ops control. Scheduling can aim at reducing the impact of minor disruptions by allocating buffer times in the right places in order to avoid propagation of delays in a rotation.

Scheduling requires block- and ground times balancing productivity and punctuality. These planning parameters should be as long as needed to be punctual, but should not be too generous thus influencing negatively the profitability of an airline. Based on historic operations data most suitable block- and ground times are defined. In addition typical constellations leading to systematic delays are identified and buffered by applying appropriate buffer on the ground.

Using operations data from different airlines over several years, we predict the lengths of ground and block times of typical operations days. Based on simulation results we assess the delay risk for each leg in a given rotation to support the scheduler in his daily work, thus enabling him to reduce the number of situations with high delay risks.

To further support scheduling in reducing delay critical situations we developed different optimizers using metaheuristic methods from the field of artificial intelligence. Starting from a given flight schedule, the aircraft routing is changed in order to improve the delay resilience as predicted by the simulation. With reasonable computation time, a significant improvement of the optimization objective can be achieved after a few iterations. By allowing small time shifts of flights, the delay risks of a schedule can be significantly decreased further.

Robust Airline Scheduling with Optimal Block and Ground Times


Airlines solve their schedule planning problem considering a little or no stochasticity and to maximize their profitability. Highly optimized schedules show an opposite trend in terms of operational metrics such as On Time Performance (OTP). We develop a simulation-based approach to measure the operability of a given schedule under various uncertainties. Schedule optimizers try to balance tradeoff between the time allocated on ground vs. flying time. Insufficient or excess ground time and block time can cause expensive delays or under-utilization of assets respectively. We aim to distribute right contingency at right places so that optimal OTP can be achieved at minimal cost. We apply an iterative framework using a mixed integer programming formulation and updating its parameters based on the simulation results. We test our approach using a major U.S. airline's daily schedule and obtain 1.81% increase in OTP without a significant decrease in profit.

Improving On-Time Performance through Robust Routing

JetBlue Airways

The talk will focus on explaining how the on-time performance and maintenance requirements can be improved with the help of robust aircraft routing. A mixed integer problem is formulated and solved which prioritizes the routes with higher buffer time in the ground turn around leg while adhering to maintenance requirements. Application of the model to the airline's schedules shows that at average 8% of the ground turn legs can be relaxed from having the minimum turn around time and can be provided an additional 10 to 20 minutes of buffer time. The maintenance schedule of the aircrafts also improves as the aircrafts touch the maintenance base more frequently with ground time long enough to carry out the periodic maintenances. All these benefits are realized without changing the schedule times therefore not requiring reduction to the aircraft utilization ratio.

Human Plus Artificial Intelligence for Robust Block Time Forecasting


Accurate block time forecasts are critical to building a reliable and profitable schedule. However, as these two metrics are opposing in nature, the planner has to balances the tradeoffs between reliability and profitability in the plan. In this talk, we present a different and novel approach to forecasting block times using Machine Learning. FICO uses historical on-time performance data and external data such as weather and airport operations to build out a feature set. Using this, we build, tune, and evaluate multiple Machine Learning models. We provide levers to the planner to then analyze the results and find the sweet spot that balances the tradeoffs between OTP and utilization before coming up with the final planned block time. As this is not a one-time exercise, we will present a decision support platform that allows the planner to work collaboratively with the ML algorithms and their human colleagues to rapidly iterate towards optimal planned schedules

Misconnect Passenger Analysis using a Visual Platform

United Airlines

Misconnecting passengers cause difficulties for our hub locations resulting in rebooking costs, protection issues, over sale situations, and reputation damage.  With a constantly moving schedule, irregular operations, and multiple connection opportunities, it is difficult to consume the large amounts of data to identify the problem(s) in misconnections.  As a result, we have developed an interactive and visual tool to help stations track progress, find most critical misconnecting city pairs, analyze past events, and recommend realistic minimum connection times based on history, location, time of day, and domestic/international types of connections.  This tool not only focuses on the immediate problem, but also the larger solution of adequately using data visualization to help identify, explain, and solve complex problems.

Leveraging Data Science to Find Punctuality Quick Wins

Air France - KLM

Punctuality has always been a major issue for carriers. Multiple business objectives tend to create and propagate delays such as decreased aircraft turn-around times to improve aircraft usage, or peaked hub activities to improve the intrinsic connectivity of networks. Our study aimed at comprehensively using Air France historical data to make out best practices that could be shared broadly. Using state-of-the-art data science techniques, we ended up following two tracks that lead us to determine simple operational levers to enhance punctuality (or at least theoretically).

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