2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
380
WA50
212-MCC
SpORts: Sports Analytics III
Sponsored: SpORts
Sponsored Session
Chair: Scott Nestler, University of Notre Dame, Mendoza College of
Business, Notre Dame, IN, 46556, United States,
1 - National Hockey League Goaltending: An Analysis Of Goaltender
Performance In Relation To Amount Of Days Rest
Paul Weisgarber, U.S. Air Force Academy, USAF Academy, CO,
United States, , Jeremy Forbes,
Luke Guinan
When deciding which goalie to start, professional hockey teams have historically
made that decision based on who the better overall goaltender is and whether
they need a night (or more) rest. Aside from coach and player intuition, little data
has been involved in such decisions. Motivated by an SB Nation article on
we attempt to better inform NHL coaches and general
managers on the relationship between the number of days rest between games
(DRBG) for a goalie, his save percentage (SV%), and team wins and losses.
2 - Analysis Of Corner Kicks In Football (Soccer)
Nils Rudi, INSEAD, , Tong Wang
Using coded events and tracking data from football matches in a major football
(soccer) league, we (1) study the prediction of the number of corner kicks in a
match statically (using only the information available before the match starts) and
dynamically (using live feed of critical events) and (2) investigate the dynamics
that convert an awarded corner kick into a goal and factors that affect the
conversion rate.
3 - Is Strength Of Schedule A Real Strength For NFL Teams
Ismail Civelek, WKU, , Murat Kurt
The National Football League (NFL) uses both complex analytical tools and panel
of experts to schedule regular season games to assure owners, coaches, players
and fans that no team has an advantage. The strength of schedule has been a
major disagreement in scheduling NFL games due to ongoing dispute about this
measure. This paper proposes a mixed-integer-linear program to investigate the
relationship between the strength of schedule and teams’ making into the play-off
and tries to answer whether the strength of schedule is a real strength for the NFL
teams.
WA51
213-MCC
Evaluating Health Systems of Public Interest
Sponsored: Public Sector OR
Sponsored Session
Chair: Andres Garcia-Arce, University of South Florida, USF,
Tampa, FL, 3, United States,
1 - Hospital Preventable Readmissions And Interventions In
Medicare Patients
Andres Garcia-Arce, University of South Florida, Tampa, FL,
United States, Jose L. Zayas-Castro
Hospital preventable readmissions in the US are considered as a target for quality
improvement by the affordable care act. Medicare uses economic penalties for
hospitals with excessive readmissions. National experts present concerns about
the appropriateness and fairness of these measurements such as the excessive
impact on safety net hospitals. The use of disease-specific interventions reduces
readmissions while directly improves the quality of care and produce savings. This
research aims to use disease-specific health interventions to reduce readmissions.
The results from this work are intended to open a discussion on alternative
policies to address preventable readmissions.
2 - Predicting Likelihood Of Drug Approval From Clinical Trials
Felipe A Feijoo, Johns Hopkins University, ,
Sauleh Ahmad Siddiqui, Jenny Bernstein
Pharmaceutical companies face huge risks and costs in order to launch a new
drug to market. These costs are associated with expensive and timely clinical trials
with a success rate that from 10% to 20%. In order to understand the drivers that
make drugs to fail at some stage of a clinical trial, we developed a machine
learning (based random forest) to determining the factors that are associated with
clinical success. Our model is capable to predict with an 85% accuracy the new
compounds that will get FDA marketing approval.
3 - The Future Burden Of CKD In China: A Simulation Model For The
CKD Initiative
Nan Chen, Tsinghua University, Room 615, Shunde Building,
Tsinghua University, Haidian District, Beijing, 100084, China,
Jinwei Wang, Xiaolei Xie, Luxia Zhang,
Li Zheng
The prevalence of chronic kidney disease (CKD) is high in China, which is
approximately 10.8% in 2010. However, awareness of CKD remains low, only
12.5% of the 119.5 million patients are aware of the condition. There exist very
few studies to estimate the future burden of CKD. We developed a CKD Health
Policy Model for Chinese people based on annual decrements in estimated
glomerular filtration rates that depend on age and risk factors. We used this
model to simulate the residual lifetime incidence of CKD and project the
prevalence of CKD in China.
WA52
214-MCC
Network Repair and Resiliency for
Service Restoration
Sponsored: Public Sector OR
Sponsored Session
Chair: Ozlem Ergun, Northeastern University, 453 Meserve,
360 Huntington Avenue, Boston, MA, 02115, United States,
Co-Chair: Aybike Ulusan, Northeastern University, 360 Huntington
Avenue, Boston, MA, 02115, United States,
1 - Network Science Based Quantification Of Resilience Of Multi-
scale Infrastructure Systems
Udit Bhatia, Northeastern University,
Natural or human-induced disruptions to multi-scale critical lifeline infrastructure
networks can damage economies and cause loss of lives. Characterizing brittleness
and guiding restoration are crucial for post-hazards recovery and proactive design.
Here we develop a quantitative network-science framework to understand
fragility and resilience of interdependent lifelines, which we demonstrate on the
interdependent Boston Mass Transit, Power transmission system by assessing
robustness and evaluating recovery strategies. Natural hazards and cyber-physical
attacks, as well as non-systematic and cascading infrastructure failures are
considered.
2 - Transportation Network Recovery Based On Multi-industry
Economic Impact
Mohamad Darayi, The University of Oklahoma, ,
Kash Barker, Nazanin Morshedlou
Freight transportation networks, considered a means to enable the flow of
commodities and to facilitate economic productivity, are prone to natural and
human-made hazards. This research pursues an approach to improve restoration
order decision making based on the broader perspective of their impact to
multiple industries and multiple regions.
3 - On The Cost Of Decentralized Scheduling For Interdependent
Network Restoration
Hongtan Sun, Rensselaer Polytechnic Institute, 110 8th St., Troy,
NY, 12180, United States, , Thomas Sharkey
We consider the problem of restoring disrupted services across multiple
interdependent networks after extreme events. The restoration efforts are usually
formulated in a decentralized manner as each system optimizes their own
restoration schedule. We consider integer programming approaches to determine
the equilibrium (stable) solutions for this decentralized scheduling system. These
approaches help to calculate the price of anarchy and the price of stability which
help to measure the loss in the centralized objective from the decentralized
scheduling process.
4 - Restoration Of Network Connectivity In Large-scale Disaster
Management Problems
Aybike Ulusan, Northeastern University, ,
Ozlem Ergun
The goal of this study is to offer enlightening insights on the network restoration
problems by developing network science based quantitative frameworks. As the
name suggests, the generic network restoration problem seeks for the best
recovery strategy for a given perturbed network. As a case study, a disrupted
network from a pot-disaster environment is tackled. Proposed frameworks are
demonstrated on the real world disrupted road networks of different cities in USA
having various topological properties.
WA50