Informs 2015

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INFORMS Philadelphia – 2015
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4 - Discovering an Unknown Network: An Optimization
Based Approach
Piya Pal, University of Maryland, Electrical and Computer
Engineering, College Park, United States of America,
A central challenge in network tomography is to discover the structure of the
network from partial observations. Depending on the type of the network, these
measurements can provide us with different kinds of information. A key question
in this regard is: how many measurements (or sensors) are needed to find out the
topology of the network, and how should they be placed? We describe a discovery
algorithm that iteratively maps the graph, by using entropy as a criterion for
sensor placement.
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02-Room 302, Marriott
INFORMS 2015 Data Mining Best Student
Paper Award
Sponsor: Data Mining
Sponsored Session
Chair: Kamran Paynabar, Georgia Institute of Technology, 755 Ferst
Drive, Atlanta, GA, 30332, United States of America,
1 - Falling Rule Lists
Fulton Wang, MIT, 5 Cambridge Center #792, Cambridge, MA,
02142, United States of America,
Falling rule lists are classification models consisting of an ordered list of if-then
rules, where (i) the order of rules determines which example should be classified
by each rule, and (ii) the estimated probability of success decreases monotonically
down the list. These kinds of rule lists are inspired by healthcare applications
where patients would be stratified into risk sets and the highest at-risk patients
should be considered first.
2 - Statistical Models for Characterizing the Heterogeneous Wake
Effects in Multi-turbine Wind Farms
Mingdi You, PhD Candidate, University of Michigan, 1205 Beal
Avenue, IOE 1773, Ann Arbor, MI, 48109, United States of
America, Eunshin Byon, Giwhyun Lee
Wind turbines in a wind farm exhibit heterogeneous power generations due to
wake effects. Because upstream turbines absorb kinetic energy in wind,
downstream turbines produce less power. Moreover, the power deficit at
downstream turbines shows heterogeneous patterns, depending on weather
conditions. This study introduces a new approach for characterizing
heterogeneous wake effects. A case study demonstrates the proposed approach’s
superior performance over commonly used alternative methods.
3 - Sparse Precision Matrix Selection for Fitting Gaussian Random
Field Models to Large Data Sets
Sam Davanloo Tajbakhsh, Visiting Assistant Professor, Virginia
Tech, 412 Hutcheson, Blacksburg, VA, 24060, United States of
America, , Serhat Aybat, Enrique Del Castillo
Fitting Gaussian random field models and finding the Maximum Likelihood
Estimate (MLE) of the parameters requires a nonconvex optimization. The
problem is aggravated in big data settings since the per iteration computational
complexity of MLE is O(n^3) where n is the number of distinct spatial locations.
We propose a theoretically provable two-stage algorithm which solves a
semidefinite program in the first stage and a least square problem in the second
stage.
4 - Sensor Driven Condition Based Generation Maintenance and
Operations Scheduling
Murat Yildirim, PhD Student, Georgia Institute of Technology,
755 Ferst Drive, Atlanta, GA, 30332, United States of America,
Nagi Gebraeel, Andy Sun
We propose an integrated framework, which combines (1) predictive analytics
methodology that uses real-time sensor data to predict future degradation and
remaining lifetime of generators, with (2) novel optimization models that
transforms these predictions into cost-optimal maintenance and operational
decisions. We present extensive computational experiment results to show
proposed models achieve significant improvements in cost and reliability.
SB03
03-Room 303, Marriott
Improving Efficiency and Effectiveness of
Supply Chains
Cluster: Scheduling and Project Management
Invited Session
Chair: Chelliah Sriskandarajah, Hugh Roy Cullen Chair In Business
Administration, Texas A&M University, 320Q Wehner, 4217 TAMU,
College Station, TX, 77843, United States of America,
1 - Outpatient Appointment Scheduling under Patient Heterogeneity
and Patient No-shows
Seung Jun Lee, PhD Student, Texas A&M University, 320N
Wehner Building, College Station, TX, 77845, United States of
America, Chelliah Sriskandarajah,
Gregory Heim, Yunxia Zhu
We study an outpatient appointment scheduling system under conditions of
patient heterogeneity in service times and patient no-shows. We contribute by
using more sophisticated sequential block scheduling policies, leading to effective
appointment schedules when scheduling two patient types. We extend our
algorithm to incorporate patient no-shows. Next, our block scheduling algorithm
is adapted where outpatient clinics use an open-access policy.
2 - A Framework for Analyzing the U.S. Coin Supply Chain
Yiwei Huang, Mays Business School, Texas A&M University,
320M Wehner Building - 4217 TAMU, College Station, TX,
77843-4217, United States of America,
Subodha Kumar, Bala Shetty, Chelliah Sriskandarajah
We present a framework of analyzing the supply side problem for increasing cost-
effectiveness of the U.S. Coin Supply Chain (CSC). We investigate the U.S. CSC
from following perspectives: new coin production in the U.S. Mint, circulating
coin distribution for the Federal Reserve System (FRS), and coin inventory
management and coin demand forecasting at coin vaults (CV). We provide an
optimal operating policy for the FRS using a minimum cost flow (MCF) network
model for multi-products.
3 - Scheduling Operating Rooms with Elective and
Emergent Surgeries
Kyung Sung Jung, University of Florida, P.O. Box 117169,
Gainesville, Fl, 32611-7169, United States of America,
Chelliah Sriskandarajah,
Vikram Tiwari
Operating rooms (ORs) generate the greatest revenue source for hospitals while
they are the largest cost centers. Scheduling ORs are challenging tasks due to the
significant uncertainty in the arrival of emergent patients. To increase the
responsiveness and efficiency for OR scheduling, we develop an optimization
model which deals with block schedules and determines the sequence of elective
patients so that the emergency patients who arrive randomly can be
accommodated without incurring delays.
4 - Operations in Currency Supply Chains – A Review
Yunxia Zhu, Rider University, Sweigart Hall 358,
Lawrenceville, KS, United States of America,
Chelliah Sriskandarajah, Neil Geismar
This paper provides an overview of studies of various currency supply chains
across the world. The structure of a general banknote supply chain is given before
the discussion of the problems from three different perspectives: the supply side,
the demand side, and the secure third-party logistics providers. We also provide a
framework for analyzing the U.S. coin supply chain and descriptions of the coin
supply chains in other countries. Future research directions are also proposed.
SB02