2016 INFORMS Annual Meeting Program

373 / 561

INFORMS Nashville – 2016
373
4 - Optimal Workload Management During A Physician’s Shift In
Emergency Departments
Zhankun Sun, University of Calgary,
ED physicians can adjust their workload, which is measured by the number of
patients signed up, to reduce patient handovers at the end of their shift. Patient
handovers raise safety concerns due to the discontinuation of care. We present a
dynamic programming model to inform patient flow management during a single
ED physician’s work shift. Case studies based on real data will also be discussed.
WA31
202C-MCC
Service Management: Economics and Operations
Sponsored: Manufacturing & Service Oper Mgmt,
Service Operations
Sponsored Session
Chair: Achal Bassamboo, Northwestern University, Kellogg School of
Management, Northwestern University, Evanston, IL, 60208,
United States,
C-Chair: Ramandeep Randhawa, University of Southern California,
Marshall School of Business, University of Southern California,
Los Angeles, CA, 90089, United States,
1 - Scheduling Networks With Synchronization Constraints And
Heterogeneous Customers
Amy R Ward, Professor, University of Southern California,
Marshall School of Business, Bridge Hall BRI 401H, Los Angeles,
CA, 90089-0809, United States,
Erhun Ozkan
Networks in which the processing of jobs occurs both sequentially and in parallel
are prevalent in many applications domains, such as computer systems,
healthcare, and manufacturing. The relevant control decision is how to
dynamically determine job priority at the servers that process multiple job types.
A key difficulty in finding a delay-minimizing control is that the parallel
processing of jobs gives rise to synchronization constraints. We propose a state-
dependent departure pacing control under which job priorities are determined so
as to balance the jobs waiting to be joined at the synchronization servers. We
prove our control is asymptotically optimal for certain network topologies.
2 - Collaboration And Multitasking In Networks: Aligning Task
Priorities And Collaboration Levels
Itai Gurvich, Kellogg School of Management,
Jan A Van Mieghem
We study networks where some tasks require the simultaneous processing by
multiple types of multitasking indivisible resources. As one maximizes capacity,
we prove, the achievable performance space collapses into a single policy.: the
highest priority must be given to the tasks that require the most collaboration: a
mismatch between priority levels and collaboration levels inevitably inflicts a
capacity loss. We further establish a fundamental difference between the
achievable performance spaces of preemptive and non-preemptive collaborative
networks.
3 - The Costs And Benefits Of Ridesharing: Sequential Individual
Rationality And Sequential Fairness
Ragavendran Gopalakrishnan, Research Scientist,
Xerox Research Centre India, Bangalore, India,
Koyel Mukherjee,
Theja Tulabandhula
We formulate a cost sharing framework for ridesharing that explicitly takes into
account the inconvenience costs of passengers due to detours. We then introduce
a notion of sequential individual rationality (SIR) that requires that the disutilities
of existing passengers decrease as additional passengers are picked up, and show
that these constraints induce a natural limit on the permissible incremental
detours as the ride progresses. We characterize routes for which there exists some
cost sharing scheme that is SIR on that route, and explore the consequences of
SIR on the design of sequentially fair cost sharing schemes. We conclude by
addressing the algorithmic challenges associated with SIR.
4 - Scheduling Impatient Customers Based on Time In Queue
Achal Bassamboo, Northwestern University,
, Ramandeep Randhawa
We study scheduling impatient customers in multi-class parallel server queueing
systems. From the system’s perspective, customers that are of the same class at
time of arrival get further differentiated on their residual patience time as they
wait in the system. Using a fluid approach, we propose a novel cost-minimizing
policy that schedules customers on two dimensions of heterogeneity: class and
time-in-queue information.
WA32
203A-MCC
Risk Analysis I
Contributed Session
Chair: Ming Zhou, Professor, Shenzhen University, College of
Management, Shenzhen, 518060, China,
1 - Optimal Capital Requirements In Financial Networks With
Fire Sales
Jongsoo Hong, Duke University, 100 Fuqua Drive, Durham, NC,
27707, United States,
We consider an interbank network with fire sales externalities of multiple illiquid
assets and study the problem of optimally trading off between capital reserves and
systemic risk. We find that the optimal capital requirements under maximum
payments and prioritized liquidation rule can be formulated as a convex and
convex mixed integer programming, respectively. To solve the convex MIP, we
offer an iterative algorithm that converges to the optimal. We show the results of
the methodology on numerical examples and provide implications for capital
regulation policy and stress test.
2 - A New Approach To Fuzzy Risk Assessing Large Renewable
Energy Construction Projects
Jose-Ignacio Munoz-Hernandez, University of Castilla - La
Mancha, Edifico Politecnico - UCLM, Avda Camilo Jose Cela, S/N,
Ciudad Real, 13071, Spain, ,
Luis Serrano-Gomez
The Fuzzy Sets Theory deals with simple linguistic terms in order to classify the
level of an impact or a probability in risk assessing. Expressions like “Moderate
Impact” or “Very High Probability” are more clear and intuitive to experts for
carrying out risk assessments than the use of numerical values. However,
idiomatic expressions are not useful to calculate severity or probability levels
accurately. This work uses Fuzzy Logic and Monte-Carlo simulation not only to
evaluate those expressions numerically but also to calculate experts evaluations
coherence, weighing up their results according to the coherence level in their
responses.
3 - Accounting For Heterogeneity And Macroeconomic Variables In
The Estimation Of Transition Intensities For Credit Cards
Jonathan Crook, University of Edinburgh, Business School,
29 Buccleuch Place, Edinburgh, EH8 9JS, United Kingdom,
, Viani Djeundje
The literature has considered intensity models that give predictions of the
probability, for each customer, that he/she will transit from one state of
delinquency to another between any two months in the life of the loan. The
transitions include not only transitions into further delinquency but also
transitions to lesser states of delinquency, that is cure. We now extend this work
by including frailty terms relating to the individual cases. This means that any
statistical bias that may exist because of the omission of unobserved effects due to
these types of variation should be removed. Results of applying the method to a
large dataset relating to credit card holders will be illustrated.
4 - Risk Strategy For Managing Information Privacy
Gwendolyn K Lee, Chester C. Holloway Professor, University of
Florida, Gainesville, FL, 32611, United States,
Ye Xia
Firms’ risk strategy involves choosing a probability of success/failure in realizing a
certain size of impact on the firm’s competitive strength. We observe a disturbing
pattern general across a broad family of shapes of risk distribution (e.g., changing
from Gaussian to Pareto distributions where the tails of the distribution become
longer or heavier). One and one firm only always chooses to take risks that carry
the possibility of inflicting extreme privacy harm. The risk strategy does not shift
as the risk-return distribution changes its shape. The risk strategy for managing
information privacy is studied in the context of firms pursuing data-intensive
innovation such as personalized medicine.
WA32