2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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TB68
Mockingbird 4- Omni
Tutorial: Wind Energy Applications
Sponsored: Quality, Statistics and Reliability
Sponsored Session
Chair: Yu Ding, Mike and Sugar Barnes Professo, Texas A&M
University, MS 3131, ETB 4016, College Station, TX, 77843,
United States,
Co-Chair: Eunshin Byon, University of Michigan, 1205 Beal Avenue,
College Station, MI, 48109, United States,
1 - Tutorial For Wind Energy Data Analytics
Yu Ding, Texas A&M University, College Station, TX, 77843,
United States, Eunshin Byon
This tutorial session discusses data analytics issues relevant to wind energy
applications. It entails three parts: ): (1) general background of wind energy and
data availability; (2) power curve modeling and turbine performance evaluation;
and (3) importance sampling and turbine reliability evaluation. The two session
chairs will be the co-presenters in this tutorial session.
TB69
Old Hickory- Omni
Decision Support Systems I
Contributed Session
Chair: Manini Madireddy, Senior Operations Research, Sabre,
3150 Sabre Dr, Southlake, TX, 76092, United States,
1 - Considering Passenger Recovery In Airline Operations Recovery
Jia Kang, Senior Operations Research, Sabre Airline Solutions,
3150 Sabre Drive, Southlake, TX, 76092, United States,
, Dinakar Gade, Sureshan Karichery
The Sabre AirCentre Recovery Manager (Ops) helps airlines quickly recover both
the schedule and aircraft rotations from various disruptions (curfews, weather,
unplanned maintenances, etc.) by taking into account operational restrictions and
several conflicting tradeoffs. In this presentation we introduce a new feature of
Recovery Manager called the Passenger Flow Module (PFM) that incorporates
passenger re-accommodation decisions during schedule recovery. The generated
solutions significantly reduce the impact to passenger flows in airline network as
well as overall passenger inconvenience.
2 - Fuzzy Association Rule Mining Framework For Product Selection
In E-Commerce
Shekhar Shukla, Doctoral Candidate, Indian Institute of
Management Lucknow, FPM H-2 Room No. 41, IIM Campus
Prabandh Nagar Off Sitapur Road, Lucknow, 226013, India,
, Ashwani Kumar
We present a robust and a unique framework of product selection that
incorporates social influence factors and provides a numerical strength of
suitability of each available product based on a customer’s set of requirements.
The Framework generates Fuzzy Association Rules based on product attributes
incorporated with customer reviews as objective weights to these attributes (using
Shannon’s Entropy) and market popularity parameters as rule implications. These
rules are used as a descriptive model for each product to perform an Association
Based Classification.
3 - A Modeling Framework For The Strategic Design Of Local Fresh
Food Systems
Hector Flores, PhD Candidate, Arizona State University,
513 W. 17th Street, Tempe, AZ, 85281, United States,
Rene Villalobos
In this work we demonstrate that certain geographical regions might have the
potential to produce high-value fresh fruits and vegetables that can be both
profitable for current farmers and can incentivize new entrants into local food
systems. Specifically, we develop an optimization-based framework that uncovers
hidden production capabilities within a region by (1) identifying needed
technologies and resources, (2) considering complementary environmental
characteristics and market price behavior, and (3) addressing logistic and supply
chain planning decisions. It also sets the framework for incorporating parameter
randomness. This work addresses research related to local food systems.
4 - Product Bundling For Airline Customers
Manini Madireddy, Senior Operations Research, Sabre,
3150 Sabre Dr, Southlake, TX, 76092, United States,
Goda Doreswamy,
Meisam Hejazi Nia, Ramasubramanian Sundararajan
We consider the problem of product bundling (seats and ancillaries) in the
context of offering the right products to the right customer at the right price and
time, in such a way as to satisfy customer needs and maximize airline revenue.
This problem falls in the realm of airline revenue management and retail e-
commerce. We present a solution approach to construct, optimize and personalize
offers to customers. We demonstrate the utility of our approach through
illustrative results on real and simulated data.
TB70
Acoustic- Omni
Transportation, Planning I
Contributed Session
Chair: Liang Wang, Phd Candidate, Harbin Institute of Technology,
Harbin, China,
1 - A Segmented Logistic Regression Model To Construct A Valid Set
Of Itineraries From A List Of Weekly Flight Legs
Anand Seshadri, Principal, Operations Research, SABRE Airline
Solutions, 3rd Floor, Navigator Building, International Tech Park,
Bangalore, 560045, India, , Gautam Pradhan
In this paper, we present a robust approach to rank and remove invalid itineraries
and retain a set of good itineraries. Traditionally, this has been accomplished by a
heuristic model. The main disadvantage of a heuristic model is that the rules are
based on the past behavior of the system and is not dynamic enough to account
for changes in airline service variables (alliances, flight departure times etc.). A
heuristic model also does not allow the modeler to eliminate itineraries during
the building stage leading to inefficient memory utilization. We calibrate the
logistic regression model based on a week of historical and schedule data for a
major US carrier and compare the results to a rule based model.
2 - Location Of Stations In A One-way Electric Car Sharing System
Hatice Çalık, Université Libre de Bruxelles, Université Libre de
Bruxelles, Boulevard du Thriomphe, Brussels, 1050, Belgium,
, Bernard Fortz
We focus on an electric car sharing system where we have a set of customers,
each of which wishes to travel from a point of origin to a point of destination at a
certain time of the day. The customers can pick up a car from a station close to
their point of origin and leave it to a station close to their destination. The
location of the stations, the customers to be served, and the stations they will visit
need to be decided in a way that maximizes the profit. We provide exact and
heuristic methods to solve the problem and conduct computational experiments
on newly generated problem instances.
3 - Spatial-temporal Crash Severity Modeling For Aging-involved
Crashes: A Case Of Interstate 95 In Florida
Aschkan Omidvar, University of Florida, Gainesville, FL, 32611,
United States, , Arda Vanli, Eren Erman Ozguven
This research aims to develop a binary logistic regression model to discover the
significant factors affecting the severe crash occurrences for aging drivers. Crash
data from two major metropolitan areas, Miami and Jacksonville, for three
consecutive years (2010-2012) are extracted, processed and analyzed using
Geographical Information Systems (GIS). These data sets are used to determine
factors influencing the severity of crashes and compare them with those for other
age groups. Next, we investigate the spatial and temporal variation of the effect of
the influential variables, on severity of aging-involved crashes by applying
variable selection on the fitted logistic regression models.
TB70