2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Deployment Guidelines For Community Health Workers In
Sub-saharan Africa
Jonas Jonasson, London Business School, London, United
Kingdom, , Carri Chan, Sarang Deo,
Jeremie Gallien
Community health workers (CHWs) are increasingly important to the delivery of
health care in many African countries. Leveraging an extensive dataset featuring
time, clinical findings and GPS information for CHW visits in Ghana, we develop
a stochastic model describing the health dynamics of a population served by a
time-constrained CHW. This model supports the design of managerial guidelines
for patient prioritization and catchment area assignment in a CHW operation.
3 - Global Vehicle Supply Chains In Humanitarian Operations:
A Network Analysis Approach
Jon M. Stauffer, Texas A&M University, College Station, TX,
United States, Alfonso J Pedraza-
Martinez, Lu Yan
We examine the vehicle supply chain network structure of the International
Federation of the Red Cross (IFRC) as they respond to a mega disaster while
continuing to support development programs and minor disasters. Using
Exponential Random Graph Models, we examine the significance of the vehicle
supply chain network changes year-to-year. Results show that temporary hubs
are utilized in mega disaster locations and that supply chain support for areas
outside the mega disaster region, while present, is reduced. This allows us to
better understand how all supply chain networks could improve their response to
large disruptions.
4 - Assessing The Impact Of Network Vulnerability On Relief
Distribution Operations Considering Social Costs
Miguel Jaller, University of California Davis,
Luis Fernando Macea, Victor Cantillo
This paper develops a model to asses the impacts that network vulnerability can
have on the distribution of critical supplies after a disaster. The model estimates
the changes in total social costs due to stochastic network disruptions. The
analyses are based on the difference between the logsum, which measures the
changes in consumer surplus or benefits, before and after the failure. In addition,
the model allows identifying the critical links in a network from the critical
response perspective.
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202A-MCC
Operations with Social Impact
Sponsored: Manufacturing & Service Oper Mgmt, Sustainable
Operations
Sponsored Session
Chair: Deishin Lee, Boston College, Chestnut Hill, MA, United States,
1 - Dynamic Staffing Of Volunteer Gleaning Operations
Erkut Sonmez, Assistant Professor, Boston College, Carroll School
of Management, Boston College, Fulton Hall, Office 350D,
Chestnut Hill, MA, 02467, United States,
Baris Ata, Deishin Lee
Gleaning refers to collecting food from what is left in the fields after harvest, and
donating the goods to food bank or pantries that serve food insecure individuals.
In this paper we study a dynamic control problem for volunteer capacity
management of gleaning operations.
2 - Strategic Commitment To A Production Schedule With Supply
And Demand Uncertainty: Renewable Energy In Day-ahead
Electricity Markets
Nur Sunar, UNC at Chapel Hill,
John R Birge
Motivated by fast penetration of variable renewable energy (such as wind and
solar energy) into the electricity generation mix, we study a day-ahead electricity
market that consists of finitely many competing firms, each facing supply
uncertainty. In electricity markets, the purpose of an undersupply penalty is to
improve reliability by motivating each firm to commit to a production schedule it
can deliver in the production stage. Using differential equations theory, we prove
that imposing or increasing a market-based undersupply penalty rate can result in
a strictly lower equilibrium reliability with probability 1. (Joint work with John
Birge)
3 - Distributed Renewable-energy Generation And Implications For
Strategic Consumer Behavior, Electricity Pricing And
Installed Capacity
Alex Angelus, UT Dallas,
We propose a continuous-time model of electricity markets, in which
heterogeneous consumers can purchase and install their own renewable-energy
generators, such as solar panels, and thus reduce electricity consumption from the
local utility. We analyze both in-the-grid and off-the grid scenarios. The optimal
time to install distributed generation follows a threshold policy on customer
demand. We derive explicit expressions for the threshold level and optimal
distributed generation to install, and determine the optimal price the utility
should charge to maximize its revenue. Contrary to the prevailing industry
practice, higher electricity prices can lead to lower revenues for the utility.
4 - Converting Retail Food Waste Into By-product
Mustafa H Tongarlak, Bogazici University, istanbul, Turkey,
, Deishin Lee
By-product synergy (BPS) is a form of joint production that uses the waste
stream from one (primary) process as useful input into another (secondary)
process. The synergy is derived from avoiding waste disposal cost in the primary
process and virgin raw material cost in the secondary process. We investigate how
BPS can mitigate food waste in a retail grocer setting, and how it interacts with
other mechanisms for reducing waste (i.e., waste disposal fee and tax credit for
food donation). We also present a hybrid approach to implementing BPS that
preserves managerial autonomy.
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202B-MCC
Joint Session HAS/MSOM-HC: Patient Flow Analytics
Sponsored: Manufacturing & Service Oper Mgmt/HAS
Healthcare Operations
Sponsored Session
Chair: Nan Liu, Columbia University, New York, NY, United States,
Co-Chair: Zhankun Sun, University of Calgary, 2500 University Dr. NW,
Calgary, AB, T2N 1N4, Canada,
1 - Models For Hospital Inpatient Operations: A Data Driven
Optimization Approach For Reducing ED Boarding Times
Shasha Han, National University of Singapore,
, Shuangchi He, Hong Choon Oh
The long ED boarding times are a threat to most public hospitals. To tackle this
problem, we examine datasets from a public hospital in Singapore and propose a
data-driven approach to optimizing bed assignments. Our formulation
incorporates practical features conventionally absent from the queueing control
framework. With a slightly increased overflow proportion, it can greatly reduce
the mean boarding times as well as the percentage of them exceeding given
targets. It also helps to resolve the time-of-day effect of boarding times, which
results from routine discharge procedures in hospitals. Interestingly, we show
there exists an optimal solution that is fair to patients within each category.
2 - An Empirical Study Of Adding Physician Assistants To Critical
Care Consultation Teams
Yunchao Xu, New York University, ,
Mor Armony, Carri Chan, Michelle Gong
Physician assistants (PAs) can sometimes be cost-effective alternatives to
physicians in healthcare systems, but their impact on critical care delivery remains
unclear. Over the course of 18 months, PAs were added to the Critical Care
Consultation team at a major urban hospital system. In new multi-period
analysis, we empirically measure the impact of part-time versus full-time PA
coverage. We find that adding PAs can reduce the average time-to-transfer for all
ICU patients and reduce mortality risk for low-severity patients. Interestingly, we
do not find evidence that the benefits of having PAs further improves patient
outcomes when adding PAs on non-weekdays.
3 - Predicting Triage Standing Orders
Han Ye, U of Illinois at Urbana-Champaign, ,
Zhankun Sun, Haipeng Shen
Overcrowding in emergency department (ED) has become a major problem
worldwide. In order to mitigate ED overcrowding, we explore the potential of
triage nurse ordering by developing models for predicting test orders using
detailed information available at the triage stage. We then study the impact and
trade-off of such predictive models in ED patient flows and patient outcomes.
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