Informs 2015

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INFORMS Philadelphia – 2015
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3 - A Chance Constrained Programming Approach to Handle
Uncertainties in Radiation Treatment Planning
Maryam Zaghian, University of Houston, 4800 Calhoun Rd,
Houston, TX, United States of America,
Azin Khabazian, Gino Lim
A chance constrained programming (CCP) framework is developed to handle set-
up uncertainties in radiation treatment planning. By allowing some degree of
violations of constraints, the proposed approach optimizes the treatment plan
while satisfying the planner’s tolerance level on the constraint violation in a
probabilistic environment. Linear deterministic equivalences of the chance
constraints are derived under distributional assumptions on uncertainties.
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34-Room 411, Marriott
Decision Models for Women’s and Children’s Health
Sponsor: Health Applications
Sponsored Session
Chair: Karen Hicklin, PhD Student, North Carolina State University,
111 Lampe Drive, Campus Box 7906, Raleigh, NC, 27695,
United States of America,
1 - Modeling Comorbidity in Women with Diabetes
Nisha Nataraj, PhD Student, North Carolina State University, 111
Lampe Drive, Campus Box 7906, Raleigh, NC, 27695, United
States of America, Fay Cobb Payton, Julie Ivy
Comorbidity is the presence of two or more concurrently existing conditions in an
individual. A 2012 CDC report estimates that one in four US adults have
comorbid conditions, contributing heavily to healthcare spending. Our focus is on
diabetes since it is associated with significant comorbidity. Using National
Inpatient Sample data (2006-2011), we build a modeling framework that helps
evaluate how comorbidity impacts prognosis and outcomes for women with
diabetes at a population level.
2 - Using Simulation to Determine a Balance between Cost and
Quality of Care for Critically Ill Infants
Emily Lada, Principal Operations Research Specialist, SAS
Institute Inc., SAS Campus Drive, Cary, NC, United States of
America, , Chris Derienzo, David Tanaka,
Phillip Meanor
Discrete-event simulation techniques are used to assess the relationship between
cost, average length of stay, and patient outcomes in a neonatal intensive care
unit (NICU). The model represents a general method that can be applied to any
NICU, thereby providing clinicians and administrators with a tool to
quantitatively support staffing decisions. Over time, the use of the model can lead
to significant benefits in both patient safety and operational efficiency.
3 - A Bayesian Markov Decision Process to Evaluate Mode of
Delivery for Laboring Women
Karen Hicklin, PhD Student, North Carolina State University, 111
Lampe Drive, Campus Box 7906, Raleigh, NC, 27695, United
States of America, , Fay Cobb Payton,
Vidyadhar Kulkarni, Meera Viswanathan, Evan Myers, Julie Ivy
A laboring woman will deliver through one of two ways: successful trial of labor
or C-section. We combine Bayesian updating into a Markov decision process to
determine under what circumstances it is appropriate to gather more information
before making a decision regarding mode of delivery. The goal is to maximize the
utility of health outcomes for the mother and child as a function of the belief that
the woman will have a safe vaginal delivery as a function of cervical dilation
progression.
MD35
35-Room 412, Marriott
Joint Session PPSN/Analytics: Pro Bono Analytics
Panel Discussion
Sponsor: Public Sector OR
Sponsored Session
Chair: David Hunt, Manager, Oliver Wyman, One University Square,
Suite 100, Princeton, NJ, 08540, United States of America,
1 - Pro Bono Analytics Panel Discussion
Moderator:David Hunt, Manager, Oliver Wyman, One University
Square, Suite 100, Princeton, NJ, 08540, United States of
America, , Panelists:
Evan Fieldston, Joel Zarrow
Pro Bono Analytics (PBA) is a new initiative within INFORMS to match members
willing to volunteer their skills with non-profit organizations working in
underserved and developing communities. To launch PBA, representatives from
prominent Philadelphia area non-profit organizations will participate in a panel
discussion exploring the types of problems they face and ways that analytics/OR
methods can help. Please join us to learn about the types of analytical problems at
non-profits, and about PBA.
MD36
36-Room 413, Marriott
Modeling Broader Policy Impacts at the Local Scale
Sponsor: Public Sector OR
Sponsored Session
Chair: Ronald McGarvey, Indust. & Manuf. Systems Engineering;
Truman School Of Public Affairs, University of Missouri, 225
Engineering Building North, Columbia, MO, 65211,
United States of America,
1 - Using Big Data to Inform Mental Health Policies
Maryam Alsadat Andalib, PhD Student, Virginia Tech, 536F
Whittemore Hall, 1185 Perry Street, Blacksburg, VA, 24061,
United States of America, , Vida Abedi,
Arash Baghaei Lakeh, Ramin Zand, Navid Ghaffarzadegan,
Niyousha Hosseinichimeh, Grant Hughes
The accuracy of survey data for analyzing health policy problems depends on
people’s willingness to admit and honestly respond to survey questions. In the
mental health context, stigma is a barrier which affects accuracy of survey data.
We investigate fidelity of using another data source, Google search queries, to
understand mental health illnesses. We specifically offer three examples of
analyzing mental health illnesses in the United States.
2 - Robust Optimization for Biopower Generation
Bayram Dundar, University of Missouri-Columbia, 200
Engineering Building North, Columbia, MO, 65211, United States
of America, , Ronald McGarvey,
Francisco X. Aguilar
The U.S. Environmental Protection Agency (EPA) has proposed a rule that aims to
reduce carbon emissions from coal-fired power plants. We develop an MILP
model to identify min-cost approaches for satisfying these proposed standards via
biopower generation subject to spatially-explicit biomass constraints. We next
propose a robust optimization model to address parameter uncertainty, and
compare the two models’ results to illustrate the impact of data uncertainty on
overall cost and emissions.
3 - Modeling the Recruitment and Retainment of Employees at a
Rural Montana Community Health Center
Andreas Thorsen, Assistant Professor Of Management, Montana
State University, 330 Jabs Hall, Bozeman, MT, 59717,
United States of America, Don Greer,
Laura Black, Edward Gamble
Community Health Centers (CHC) are not-for-profit health care corporations
which provide comprehensive medical and dental care for their communities
regardless of the individual’s insurance coverage or ability to pay. For a CHC in
rural Montana, there are unique challenges related to recruitment and retention
of highly qualified, mission-driven employees. We identify and address these
challenges using a system dynamics modeling approach.
4 - Technoeconomic and Policy Considerations for Large-scale Solar
Deployment in India
Aimee Curtright, Senior Physical Scientist, RAND Corporation,
4570 Fifth Ave, Suite 600, Pittsburgh, PA, 15213, United States of
America, , Zhimin Mao, Oluwatobi Oluwatola,
Mridula Dixit Bharadwaj
The SERIIUS consortium aims to develop and assess PV and CSP solar
technologies that can support India’s ambitious solar deployment goals, recently
increased to a target of 100 GW by 2022. RAND and CSTEP are collaborating to
conduct technoeconomic and policy analyses to support the SERIIUS consortium.
This presentation will discuss recent and ongoing work, including progress made
by U.S.-based Pardee RAND students during their visiting internships at CSTEP in
India.
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