2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - A Multi-response Multilevel Model With Application In Nurse Care
Coordination
Bing Si, Arizona State University, Tempe, AZ, United States,
Jing Li
Nurse care coordination plays a vital role in promoting patient outcomes. The
recently developed Nurse Care Coordination Instrument (NCCI) enables
quantitative data to be collected on nurses’ coordination activities, demographics,
workload and practice environment. Driven by this, we propose a novel multi-
response multilevel model with joint fixed/random effect selection across multiple
responses and apply it to a dataset collected across four U.S. hospitals using the
NCCI. Our study conducts the first quantitative analysis linking multiple care
coordination metrics with multilevel predictors and thus provides important
insight into how care coordination might be impacted or improved.
3 - Optimal Expert Knowledge Elicitation For Bayesian Network
Structure Identification
Yan Jin, University of Washington, Seattle, WA, United States,
, Cao Xiao
This talk is about a systematic approach that combines observational data and
expert knowledge to better learn the influential relationships between variables
for networked systems, as well as automates the expert elicitation process and
collect the most informative expert knowledge, optimally matched to the
observational data, to improve the learning of the BN structure.
Applications include event cascade modeling of Alzheimer’s disease and human
resource management key performance indicator measurement.
4 - Temporal Monitoring Of Dynamic Attributed Networks
Mostafa Reisi, Georgia Tech,
We consider the problem of change detection in dynamic attributed networks.
First, networks are modeled through a generalized linear model (GLM). Then, a
state-space model is built by considering a linear state model over the parameters
of the GLM. Extended Kalman filter is used for estimating and predicting the
parameters of the state-space model. For each upcoming network, a Pearson
residual based on the actual network and its prediction is calculated. The Pearson
residuals are monitored through an EWMA control chart. Comparison of this
method with its static counterparts shows significant improvement in detecting
changes.
SB03
101C-MCC
Nicholson Student Paper Prize II
Invited: Nicholson Student Paper Prize
Invited Session
Chair: Maria Esther Mayorga, North Carolina State University, 400
Daniels Hall, Dept. of Industrial & Systems Engineering, Raleigh, NC,
27695, United States,
1 - Nicholson Student Paper Prize
Maria Esther Mayorga, North Carolina State University,
Dept. of Industrial & Systems Engineering, Raleigh, NC, 27695,
United States,
This session highlights the finalists for the 2016 George Nicholson Student Paper
Competition.
2 - Robust Monotone Submodular Function Maximization
Rajan Harish Udwani, James B. Orlin, Andreas S. Schulz,
Massachusetts Institute of Technology, Cambridge, MA,
We consider a robust formulation, introduced by Krause et al. (2008), of the
classical cardinality constrained monotone submodular function maximization
problem, and give the first constant factor approximation results. The robustness
considered is w.r.t. adversarial removal of up to \tau elements from the chosen
set. We give both, fast and practical approximation algorithms with sub-optimal
guarantees as well as more theoretical ones achieving the best possible guarantee.
Finally, we also give a black box result for the more general setting of robust
maximization of monotone submodular functions subject to an independence
system.
3 - A Constant-Factor Approximation For Dynamic Assortment
Planning Under The Multinomial Logit Model
Ali Aouad, Massachusetts Institute of Technology, Cambridge, MA,
Abstract to come
4 - Delay, Memory, and Messaging Tradeoffs in Distributed Service
Systems
Martin Zubeldia, Massachusetts Institute of Technology,
Cambridge, MA, Contact:
Abstract to come
SB04
101D-MCC
Energy Storage and Virtual Trading in the Smart Grid
Sponsored: Energy, Natural Res & the Environment, Energy I
Electricity
Sponsored Session
Chair: Miguel F Anjos, Polytechnique Montreal, C.P. 6079,
Succ. Centre-ville, Montreal, QC, H3C 3A7, Canada,
1 - Optimizing Energy Flows For A Grid Connected Smart House
Producing Renewable Energy
Luce Brotcorne, INRIA,
Ekaterina Alekseeva, Michel Gendreau, Mohammed Skiredj
We focus on optimizing energy flows for demand management of a grid
connected smart house equiped with a system combining photovoltaic electricity
and battery . The smartly scheduled way of using, storing, generating, buying and
selling energy allows customers to reduce electricity payments, to be less
dependent on the grid and avoid creating peak power demand in the grid. We
propose a stochastic mathematical linear program to make an optimal decision
with the lack of perfect information related to purchasing electricity prices and
energy produced by PV generator.
2 - Capacity Expansion Modeling For Storage Technologies
Elaine Thompson Hale, Senior Engineer, National Renewable
Energy Laboratory, Golden, CO, United States,
, Brady Stoll, Trieu Mai
The Resource Planning Model (RPM) is a capacity expansion model designed for
regional power systems and high levels of renewable generation. Recent
extensions capture value-stacking for storage technologies, including batteries and
concentrating solar power with storage. After estimating per-unit capacity value
and curtailment reduction potential, RPM co-optimizes investment decisions and
reduced-form dispatch, accounting for planning reserves; energy value, including
arbitrage and curtailment reduction; and three types of operating reserves.
Multiple technology cost scenarios are analyzed to determine level of deployment
in the Western Interconnection under various conditions.
3 - Optimizing Storage Operations In Transmission-constrained
Networks For Medium And Long-term Operation
Diego Alejandro Tejada Arango, Universidad Pontificia Comillas,
IIT, Madrid, Spain,
Sonja Wogrin, Efraim Centeno
The main objective is to present a new approach to model the storage operation
in the context of Medium- and Long-Term Operational Planning (MLTOP). This
approach is based on the system-state framework but including transmission
constraints. A DC power flow approach is used to represent the transmission
network. The methodology is related to clustering techniques using information
such as demand and wind generation per node. Case studies are presented in
order to compare the newly proposed methodology and the hourly approach. The
results illustrate the computational time reduction without loss of accuracy in the
solution.
4 - A Model Of Virtual Trading And The Forward Day Ahead Market
Gauthier De Maere D’Aertrycke, GDF Suez, Boulevard Simon
Bolivar 34, Brussels, Belgium,
Yves Smeers, Andreas
Ehrenmann
The day ahead market plays an ambiguous role in restructured electricity
markets. It is meant to help physical transactions such as the starting of machines
in the unit commitment but is also intended to be a forward market capable of
transferring the vagaries of real time prices into forward prices. Virtual trading
was introduced for that purpose. We provide a model of virtual trading and give
conditions for achieving the objective. We discuss what those conditions would
imply in case of important penetration of decentralised energy. We also show
some numerical experiment.
SB04