Informs 2015

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INFORMS Philadelphia – 2015
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7 - Intersection of a Tree Network for the Single Refueling Station
Location Problem
Sang Jin Kweon, PhD Student, The Pennsylvania State
University, 310 Leonhard Building, State College, PA, 16802,
United States of America,
An intersection is the vertex whose degree is greater than two in the network. In
this talk, we consider intersections and develops the methodology that determines
the continuous interval of the potential locations for a single alternative-fuel
refueling station on a tree network, with an objective of maximizing the amount
of traffic flows in round trips per time unit captured by the station.
8 - Intelligent Tutoring Systems: Future Paradigm of
Educational Environments
Alireza Farasat, University at Buffalo (SUNY), 4433 Chestnut
Ridge Rd Apt. 7, Amherst, NY, 14228, United States of America,
Alexander Nikolaev
Educational systems have witnessed a substantial transition from traditional
educational methods mainly using text books, lectures, etc. to newly developed
systems which are artificial intelligent-based systems and personally tailored to
the learners. We have developed a web-based tool, Crowdlearning which
concentrates on creating an intelligent system that learns to interact with students
and motivates them to more actively participate in the learning process by
proposing their own problems.
9 - Optimized Scheduling of Sequential Resource Allocation Systems
Ran Li, PhD Student, Georgia Institute of Technology, 755 Ferst
Drive NW, Atlanta, GA, 30332, United States of America,
, Spyros Reveliotis
We consider the scheduling problem of allocating finite reusable resources to
concurrent sequential processes. This problem also involves the logical issue of
deadlock avoidance. Our approach is based on the formal model of the
generalized stochastic Petri-net. Special emphasis is placed on the representational
and computational complexity of the proposed methods, which are controlled
through (i) a pertinent (re-)definition of the target policy spaces, and (ii)
simulation optimization.
10 - Operation Research for Data Mining: An Application to
Medical Diagnosis
Shahab Derhami, Auburn University, 3301 Shelby Center,
Auburn, GA, 36849, United States of America,
Fuzzy rule based classification systems (FRBCSs) have been successfully employed
as a data mining technique where the goal is to discover the hidden knowledge in
a data set and develop an accurate classification model. Despite various heuristic
approaches that have been proposed to learn fuzzy rules for these systems, no
exact optimization approach has been developed for this problem. We propose
integer programming models to learn fuzzy rules for a FRBCS used for medical
diagnosis purpose.
11 - Forecasting Surges in the Hospital Emergency Department (ED)
Alexander Gutfraind, Chief Healthcare Data Scientist, Uptake
Technologies, 600 W. Chicago Avenue, Chicago, IL, 60654, United
States of America, , Nelson Bowers,
Jim Herzog, Madeline Jannotta, Ilan Kreimont,
Adam Mcelhinney
A major hospital system in the Chicago metro area experiences large unexpected
surges in its Emergency Department (ED).
Using five years of ED admissions we predict ED surges and improve scheduling
of staff.
Data indicates the time of arrival, rooming and discharge and acuity. Total arrivals
per day cannot be predicted accurately with epidemiological climatological,
calendar variables but the state of the ED could be predicted 1-4 hours in advance
with high accuracy using VAR methods.
12 - A New Measure for Testing Independence
Qingcong Yuan, Graduate Student, University of Kentucky, 300
Alumni Drive Apt. 166, Lexington, KY, 40503, United States of
America, , Xiangrong Yin
We introduce a new measure for testing independence between two random
vectors. Our measure differs from that of distance covariance, by using expected
conditional difference of characteristic functions. We propose one empirical
version by slicing on one of the random vectors. This empirical measure is based
on certain Euclidean distance. Its properties, asymptotics and applications in
testing independence are discussed. Implementation and Monte Carlo results are
also presented.
13 - Graph Based Non-isometric Curve to Surface Matching for
Local Calibration
Babak Farmanesh, PhD Student, Oklahoma State University,
322 Engineering North, Stillwater, OK, 74078-5016, United
States of America, ,
Balabhaskar Balasundaram, Arash Pourhabib
Calibration refers to the process of adjusting parameters of a computer simulation
so that the simulation responses match the corresponding physical responses.
Calibration can be interpreted as a curve to surface matching problem. We
propose a graph-theoretic non-isometric matching approach to solve this problem
using the graph shortest path algorithm in one-dimensional spaces. For higher
dimensional spaces, we introduce the generalized shortest path concept to solve
the matching problem.
14 - Location and Coverage Models for Preventing Attacks to
Interurban Transportation Networks
Ramón Auad, Associate Professor, Universidad Católica del Norte,
Of. 318, Bldg. Y1, 0610 Angamos Avenue, Antofagasta, 1240000,
Chile, Rajan Batta
We develop a binary integer programming model to solve this problem, whose
objective is to maximize the expected vehicle coverage across the network over a
time horizon, using decomposition heuristics. To introduce a measure of equity,
we propose two sets of time constraints, considering total vehicle coverage,
inequity and network coverage. We explore scalability of the model for
excessively large instances. All of this features are applied to a case study in
Northern Israel.
15 - An Information-based Framework for Incorporating Travel Time
Uncertainty in Transportation Modeling
Jiangbo Yu, University of California, Irvine, 4101 Palo Verde Rd,
Irvine, CA, 92617, United States of America, ,
Jay Jayakrishnan
This paper proposes a modeling framework aimed at systematically incorporating
perceived uncertainty into decision making. The model uses theoretically sound
concepts from information theory, communication, and cognitive science.
Potential applications and implications are identified and demonstrated with
examples.
16 - Database of Identified Poly and Mono ADP-ribosylated Proteins
Charul Agrawal, Undergraduate Student, Indian Institute of
Technology (IIT) Delhi, Room No ED-16, Himadri Hostel, Hauz
Khas, New Delhi, 110016, India,
Poly(ADP-ribose) polymerase (PARP) is a family of enzymes with 17 known
members regulating post translational modification of proteins by attaching a
single ADP ribose unit (MARylation) or a chain of ADP ribose (PARylation).In this
study we have attempted to identify all proteins known to be modified by PARPs
and the methods as well as drugs used in such studies. Our study aims to create
the first ever tool for characterizing these modifications.
17 - Configuring Ecommerce Driven Supply Chains in the
FMCG Sector
Stanley Lim, PhD Candidate, Cambridge University, Department
of Engineering, 17 Charles Babbage Road, Cambridge,
United Kingdom,
Omnichannel has become the engine of growth in retailing. However, it remains
unclear as to how distribution networks should be configured. This research will
shed light through a framework development, and by drawing theories from
supply chain configuration, resource based view, and transaction cost economics.
Case study approach is adopted to identify the critical factors driving operational
choices and seeks to elaborate the relationships between configuration, capability
and performance.
18 - Benchmarking Construction and Improvement Heuristics for
Classification using Markov Blankets
Daniel Gartner, Carnegie Mellon University, 5000 Forbes Avenue,
Pittsburgh, PA, 15213, United States of America,
Rema Padman
This study examines construction heuristics in connection with a tabu search-
based improvement heuristic for classification in high dimensional data sets.
Using the UCI machine learning data repository containing benchmark instances
in e.g. health care, we evaluate computation times and information about the
evolution of the Markov blanket graphical models in each phase of the heuristics.
We compare the performance of the approaches using evaluation measures such
as classification accuracy.
19 - A Sim-heuristic Algorithm for Robust Vehicle Routing Problems
with Stochastic Demand
Abdulwahab Almutairi, Technology, 9 Horizon Building,
Portsmouth, PO4 8EW, United Kingdom,
We consider the VRPSD in which customers’ demands are stochastic. We propose
to model and solve the VRPSD by developing a robust optimisation model with a
sim-heuristic solution method to minimise the cost while satisfying all demands.
The method combines MCS with CWS in order to efficiently solve the VRPSD
combinatorial optimisation problem. The results is generating very good quality
solutions compared to those in the literature.
POSTER SESSION