2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
181
Two-stage Game Theoretic Modeling Of Airline Frequency And
Fare Competition
Reed Harder, Dartmouth College, 14 Engineering Drive,
Hanover, NH, 03755, United States,
, Vikrant Vaze
We develop a 2-stage game-theoretic model of airline competition, with flight
frequency decisions followed by fare decisions. For a simple 2-player model, we
show that this game has properties that ensure a tractable and credible
equilibrium solution. We then use quadratic approximations of payoffs to extend
these results to more realistic scenarios. Finally, we calibrate model parameters on
a real-world network and validate out-of-sample predicted frequencies against
observed airline behavior.
Identification And Allocation Of Increased-risk
Encephalitis Organs
Pinar Keskinocak, Georgia Institute of Technology, School of
Indust/System Eng, 765 Ferst Drive, Atlanta, GA, 30332,
United States, , Hannah Smalley,
Nishi Anand, Dylan Buczek, Nicholas Buczek, Tim Lin,
Tanay Rajore, Muriel Wacker, Brian Gurbaxani,
Matthew Kuehnert, Sridhar Basavaraju, Teresa Hammett
We developed decision-support tools to aid organ transplant physicians (and
patients) in the identification and allocation of organs that carry the risk of
infectious encephalitis. The Infectious Encephalitis Risk Calculator assesses
whether a donor (and his/her organs) may have infectious versus non-infectious
encephalitis. The Liver Transplant Decision Aid helps patients and physicians
evaluate the trade-offs between accepting and rejecting an increased-risk
encephalitis liver, thus potentially enabling a better allocation of high-risk organs
and reducing deaths on the waitlist. The tool provides wait time estimates for liver
transplants based on patient characteristics.
Evaluation Of Google’s Voice Recognition And Sentence
Classification For Health Care Applications
M. Majbah Uddin, University of South Carolina, 300 Main Street,
Civil and Environmental Engineering, Columbia, SC, 29208,
United States, , Nathan Huynh, Jose M Vidal,
Kevin M Taaffe, Lawrence Fredendall, Joel S Greenstein
This study examined the use of voice recognition (VR) technology in
perioperative services (Periop) to enable Periop staff to record workflow
milestones using mobile technology. The use of mobile technology to improve
patient flow and quality of care could be facilitated if such VR technology could
be made robust. The goal of this experiment was to allow the Periop staff to
provide care without being interrupted with data entry and querying tasks. This
study enhanced Google’s VR capability by using post-processing classifiers (i.e.,
bag-of-sentences, support vector machine, and maximum entropy), which would
facilitate its use in health care and other applications.
A Heuristic Algorithm Assigning Optimal Tolls
Vyacheslav V. Kalashnikov, Tecnologico de Monterrey,
ITESM, Campus Monterrey, Ave. Eugenio Garza Sada 2501 Sur,
Monterrey, 64849, Mexico,
Nataliya I. Kalashnykova, Arturo García-Martínez
The problem of assigning optimal tolls to the arcs of a multi-commodity
transportation network is formulated as a bilevel mathematical program. We
describe an algorithm based on the allowable ranges to stay optimal (ARSO)
resulting from sensitivity analysis applied to the lower level problem. In this way,
one can analyze possible changes in the coefficients of some variables in the
objective function within these allowed ranges without affecting the optimal
solution. In addition, when stuck to a local maximum solution, the “filled
function” technique helps one “jump” to another local maximum (if such does
exist) or stop the search. Numerical experiments confirm the robustness of our
heuristics.
Developing A Novel Inventory Classification Approach For Large
Scale Multi Echelon Inventory Systems
Alireza Sheikhzadeh, University of Arkansas, 4207 Bell
Engineering Center, Fayetteville, AR, 72701, United States,
, Manuel D Rossetti
The purpose of this research is to create a new inventory classification approach
for large-scale multi-echelon repairable item provisioning systems. In this
research, we develop a new concept for defining the classification criteria which is
the artificial stocking policy (ASP). We also propose a new partitioning approach
which takes into the account the characteristics of the (aggregated) pseudo-items.
The proposed technique is evaluated and compared with complete enumeration
and eight alternative clustering and classification methods via 36 different
problem instances. The results indicate that the proposed methods significantly
outperform the alternative techniques.
The Value Of Aggregation Under Minimax Pricing Scheme In The
Electricity Retail Market
Alberto J Lamadrid, Associate Professor, Lehigh University, 621
Taylor Street, R451, Bethlehem, PA, 18015-3120, United States,
, Kwami Senam Sedzro, Mooi Choo Chuah
We explore both economic and technical benefits of demand responsive load
aggregation under a specific retail pricing scheme we call Minimax. It is a 3-rate
scheme with a threshold level. Each region is applied a differentiated rate. To
assess how adopting Minimax would impact both end-users and distribution
system operators (DSO), we model consumers’ optimal response to Minimax as
an MILP and evaluated the DSO’s operating conditions and costs. A case study
with different aggregation scenarios implemented on the IEEE 33-bus system
reveals that larger aggregate groups achieve lower energy bills and help the DSO
lower generation cost and aggregate peak demand, and achieve better voltage
profiles.
Designing A Space-efficient Warehouse Layout
Shahab Derhami, PhD Candidate, Auburn University,
3301 Shelby Center, Auburn, AL, 36849, United States,
rey Smith, Kevin Gue
In this research, we analyze the factors that impact the space utilization in a
warehouse. We develop mathematical models to maximize space utilization in the
warehouse and depict the trade-off exist between space utilization and
transportation cost in the warehouse layout.
Optimizing Decisions In Prenatal Integrated Screening For
Down Syndrome
Jia Yan, Georgia Institute of Technology, 710 Peachtree Street NE,
Apt 1612, Atlanta, GA, 30308, United States,
Turgay Ayer, Pinar Keskinocak, Aaron Caughey
Down syndrome (DS) is a common type of chromosomal abnormality. Currently
a one-size-fits-all type of risk-cutoff value of 1/270 is commonly used in DS
screening to identify high-risk women and recommend an invasive confirmatory
test, such as amniocentesis. In this study, we construct modeling frameworks to
determine the optimal cutoffs from two practical perspectives of DS screening:
one is the fairness across ages, and the other is the heterogeneity in women’s
preferences about adverse pregnancy outcomes. We have shown the potential to
improve health outcomes and patient satisfaction.
Identification Of Optimal Partition For Semidefinite Optimization
Ali Mohammad Nezhad, PhD Candidate, Lehigh University,
200 West Packer Ave, Bethlehem, PA, 18015, United States,
Tamas Terlaky
The concept of optimal partition was originally introduced for linear optimization
and linear complementary problems and subsequently extended to semidefinite
optimization. In this paper, under no assumption on strict complementarity, we
formalize the optimal partition concept for semidefinite optimization. The
magnitude of the eigenvalues belonging to each partition is quantified using a
condition number and the degree of singularity of the problem.
Wasserstein Distance And The Distributionally Robust Tsp
Mehdi Behroozi, Assistant Professor, Northeastern University, 334
Snell Engineering Center, 360 Huntington Avenue, Boston, MA,
02115, United States,
Recent research on the robust and stochastic Euclidean travelling salesman
problem has seen many different approaches for describing the region of
uncertainty, such as taking convex combinations of observed demand vectors or
imposing constraints on the moments of the spatial demand distribution. In this
paper, we consider a distributionally robust version of the Euclidean travelling
salesman problem in which we compute the worst-case spatial distribution of
demand against all distributions whose Wasserstein distance to an observed
demand distribution is bounded from above. This constraint allows us to
circumvent common overestimation that arises when other procedures are used.
Reformulating The Disjunctive Cut Generating Linear Program
Thiago Serra, Carnegie Mellon University, 5000 Forbes Ave,
Pittsburgh, PA, 15213, United States, , Egon Balas,
Francois Margot
In lift-and-project, CGLP optima may yield dominated cuts due to distortions
caused by normalization. This work proposes the Reverse Polar CGLP, a
reformulation where normalization defines separability and the resulting cut
minimizes the slack for a point in the disjunctive hull. Cuts derived from RP-
CGLP optima define supporting hyperplanes of the disjunctive hull, hence never
being strongly dominated. For a point in the interior of the disjunctive hull, the
cutting plane is a combination of facets separating the fractional solution. We
show equivalent CGLP formulations, explain the benefits of RP-CGLP, and
present computational experiments where a larger gap can be closed after two
rounds.
POSTER COMPETITION