2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
489
WE18
106A-MCC
DMA Machine Learning
Contributed Session
Chair: Hang Li, Pennsylvania State University, University Park, PA,
United States,
1 - Risk Prediction On Life Insurance Lapse
Ceni Babaoglu, Dr., Ryerson University, Ryerson University, 350
Victoria Street, Toronto, ON, M5B 2K3, Canada,
Atakan Erdem, Ayse Bener
Lapse constitutes a material risk for life insurance companies and needs to be
controlled and managed carefully. In this project, we study the risk prediction on
life insurance lapse of an insurance company. The data that we mine includes
demographics, household income, unemployment and geographical information
of the clients. We build a model for the prediction of lapse by using machine
learning techniques.
2 - Visualization Strategies For Prediction And Classification In
Supervised Machine And Statistical Learning
Alexander Engau, Associate Professor, University of Colorado
Denver, Denver, CO, United States, ,
Paola Gonzalez
Supervised machine and statistical learning is a key task in data mining and many
areas of human decision making including finance, business and industry as well
as health care, medicine and bioinformatics. To facilitate a better understanding of
current classifiers for prediction whose performances are typically measured and
compared only numerically using cross validation, here we present a novel idea
for an additional and much more meaningful visualization. We also report its
recent use in two financial and medical case studies for substantial new insights
into several current state-of-the-art implementations of support vector machines,
decision trees, boosting and discriminant analysis.
3 - An Anomaly Detection Algorithm Using Tree-based Phase Space
Method
Cheng-Bang Chen, Penn State University, 445 Waupelani Dr.,
Apt K18, State College, PA, 16801, United States,
The cost of out of control events is usually extremely high, but the anomaly
patterns are sometimes hard to detect because of the nonlinear and the high
dimensional signal. Current methods focus on single signal source or
dimensionality reduction, but it decreases the accuracy and sensitivity. We
propose an efficient method to detect the anomaly patterns in high
dimensionality accurately, using the q-tree structure for phase space, and a tree
structure indexing for the subsequence signals.
4 - Optimal Experimental Design On Non-euclidean Spaces For
Active Learning
Hang Li, Pennsylvania State University, University Park, PA,
United States, Enrique Del Castillo,
George Runger
An Active Learning (AL) strategy selects instances to label in order to improve a
model with a relatively small number of queries, accelerating learning. In recent
years a number of machine learning authors have noticed the similarities
between AL used for linear models and the optimal experimental design problem.
In this presentation we will discuss optimal experimental design for active
learning in curved spaces. A double penalized least squares functions leads to a
generalization of the notions of alphabetic optimality in classical optimal design.
The impact of these penalization parameters on the designs are discussed.
Extensions to other types of non-euclidean spaces will be discussed.
WE19
106B-MCC
Opt, Heuristic Programming
Contributed Session
Chair: McKenzie Worden, CUBRC, Inc., 4455 Genesee St., Suite 106,
Buffalo, NY, 14225, United States,
1 - Quay Crane Scheduling Problem With Considering Tidal Impact
And Fuel Consumption
Yu Shucheng, Doctor, Shanghai University, Shang Da Road 99,
Shanghai 200444, China, Shanghai, 200444, China,
This study investigates a quay crane scheduling problem with considering the
impact of tides in a port and fuel consumptions of ships. A mixed-integer
nonlinear programming model is proposed. Some nonlinear parts in the model
are linearized by approximation approaches. For solving the proposed model in
large-scale problem instances, both a local branching based solution method and a
particle swarm optimization based solution method are developed. Numerical
experiments with some real-world like cases are conducted to validate the
effectiveness of the proposed model and the efficiency of the proposed solution
methods.
2 - A Cross Entropy Approach To The Single Row Facility
Layout Problem
Xiu Ning, Tsinghua University, Shunde Building, Room 519A,
Beijing, 100084, China,
The single row facility layout problem (SRFLP) is to arrange a given number of
facilities along a straight line so as to minimize the total cost associated with the
interactions between the facilities. In this paper, a metaheuristic algorithm based
on the cross-entropy (CE) method is developed to solve this problem. To speed up
the convergence of the algorithm, we incorporated local search procedures and
symmetry breaking techniques with the CE method. The proposed algorithm has
been tested using the instances available in the literature. The computational
results show that the proposed algorithm can find the best solutions obtained so
far for instances with up to 100 facilities.
3 - Coordinated Dynamic Demand Lot Sizing And Delivery
Scheduling Problem With Resource Restriction
Rui Liu, PhD, Huazhong University of Science and Technology,
Wuhan, 430073, China, , Lin Wang
Coordinated strategy is often used to cut down cost and increase profit in supply
chain management. A new coordinated dynamic demand lot sizing and delivery
scheduling problem with resource restriction is proposed and formulated. The
delivery policy is integrated into coordinated dynamic demand lot sizing problem
with resource restriction. In fact, the proposed model is more practical.
4 - Optimal Communication Of Information For Warfighter Benefit
Azar Sadeghnejad, Buffalo, 157 Ranch Trail, Williamsville, NY,
14221, United States, , Michael Hirsch,
Hector Juan Ortiz-Pena
There has been a significant increase in the number of sensors deployed to
accomplish military missions. These sensors might be on manned or unmanned
resources, and might collect quantitative and/or qualitative information
important for mission success. Of critical importance for mission success is
ensuring that the collected information is routed to the people/systems that need
the information for the proper making of decisions. This research mathematically
formulates the problem of information routing and collection on a temporally
varying communication network, and discusses some heuristics for efficient
solutions.
5 - Optimization Of Information Collection And Distribution Across
A Limited Communications Network
McKenzie Worden, CUBRC, Inc., 4455 Genesee St., Suite 106,
Buffalo, NY, 14225, United States,
Azar Sadeghnejad, Chase Murray, Mark Henry Karwan,
Hector Juan Ortiz-Pena
For this problem, we aim to develop a heuristic that defines information
collection and exchange between unmanned resources and a control station.
Decisions will be made determining the routes of each resource, as well as the
areas from which their sensors will collect information. Considering bandwidth
and communication range restrictions, the heuristic will determine when
collected information will be sent back to the control station. We will also
consider scenarios in which resources may send information amongst each other,
as relays, prior to the ground station receiving the information.
WE20
106C-MCC
Health Care, Other I
Contributed Session
Chair: Jingyun Li, Assistant Professor, California State University -
Stanislaus, 1 University Circle, Turlock, CA, 95382, United States,
1 - The Lag In Service Encounter: Indian Healthcare
Insurance Context
Sudipendra Nath Roy, Fellow Program in Management, Indian
Institute of Management, Indore, Prabandh Shikhar,
Rau- Pithampur Road, Indore, 453331, India,
, Bhavin J Shah, Hasmukh Gajjar
Indian healthcare service providers primarily operate through third party
administrator (TPA) for bill settlement for the services that are covered under a
paid medical insurance cover. Patients usually have to wait for more than
acceptable time for final settlement because of coordination inefficiencies between
TPA and hospital administration. This study explores the potential process
improvement to overcome such delays in Indian tertiary hospital setting.
WE20