Informs 2015

330 / 552

INFORMS Philadelphia – 2015
328
2 - Appointment Scheduling and Overbooking to Improve Patient
Access and Reduce Patient Backlog
Linda Laganga, Vp Of Quality Systems, Mental Health Center of
Denver, 4141 East Dickenson Place, Denver, CO, 80302, United
States of America, Stephen Lawrence
Patient no-shows continue to trouble outpatient clinical service delivery. We
continue our piloting and implementation of scheduling models developed in our
earlier research to develop new techniques to assist clinics in meeting their goals
to improve patient flow and reduce backlog in scheduling. We utilize medical
practice experience to develop realistic estimates of costs and their effect on the
selection of high-performing scheduling alternatives.
3 - Improving HIV Early Infant Diagnosis Supply Chains in
Sub-Saharan Africa: Models and Application to Mozambique
Jonas Jonasson,Student, London Business School, Regent’s Park,
London NW1 4SA, United Kingdom, ,
Sarang Deo, Jérémie Gallien
Most countries in sub-Saharan Africa experience delays in HIV early infant
diagnosis (EID). We develop a two-part modeling framework to generate
operational improvements in EID networks and evaluate their impact on public
health. For the case of Mozambique, we estimate that the interventions of
optimally re-assigning clinics to labs and optimally re-allocating diagnostic
capacity would result in 11% and 22% shorter turnaround times and 4% and 7%
more infants starting treatment, respectively.
TC30
30-Room 407, Marriott
Decision Support Systems I
Contributed Session
Chair: Mohamad Hasan, Associate Professor, Kuwait University,
Department of Quantitative Methods &IS, CBA,Kuwait University,
Kuwait City, 13055, Kuwait,
1 - Review of Consistency Among Pairwise Comparisons:
Relationship Between Indices and Human Perception
Yuji Sato, Graduate School of Management, Chukyo University,
101 Yagotohonmachi, Showa, Nagoya, 466-8666, Japan,
This paper reviews the Consistency Index (CI) of AHP. Since AHP requires
redundant pairwise comparisons, transitivity in judgment is often violated. The
review focuses on the detection capability of CI, and the relationship between the
size of CI and the goodness-of-fit of weight to decision maker’s perception. The
results imply that CI may not distinguish the consistency of judgment nor the size
may have no relation with the degree of goodness-of-fit of weight to decision
maker’s perception.
2 - Transformations and Materializations of Uncertainty Sets in
Robust Optimization
Abhilasha Aswal, International Institute of Information
Technology, Bangalore, 26/C Electronics City, Bangalore, KA,
560100, India, Prasanna Gns
We present a polyhedral representation of uncertainty for robust optimization and
a volume based uncertainty measure for it. Our decision support framework
enables easy transformations and materializations of a given uncertainty set and
also easy set-theoretic operations on alternative uncertainty sets. These operations
are quite useful in practice and are more difficult with probabilistic
representations of uncertainty and non-polyhedral robust uncertainty sets.
3 - Open Source or Proprietary? A Study on Software Diffusion in a
Competitive Market
Chao Ding, Assistant Professor, University of Hong Kong, KKL
807, Hong Kong, Hong Kong - PRC,
When choosing between open source software and proprietary software,
consumers will consider software quality, cost, consumer reviews, promotions,
compatibility, technical support, ease of use, etc. In this paper, we consider three
important decision making factors as identified in literature: external influence,
internal influence and ownership cost and study their impact on consumers’
adoption decision.
4 - A Decision Support System for Predicting International Freight
Flows for Trade
Mohamad Hasan, Associate Professor, Kuwait University,
Department of Quantitative Methods &IS, CBA, Kuwait City,
13055, Kuwait,
A decision support system is developed that can help decision makers to take right
decisions about the country international trade system. It helps them to evaluate
deferent scenarios to improve the multimodal Transport system and import,
export, re-export, and transit operations. These improvements will enhance the
competitiveness and integration of this system.The overall results will help in
increasing the international trade share for the country.
TC31
31-Room 408, Marriott
Joint Session DM/QSR: Quality and Statistical
Decision Making in Health Care Applications
Sponsor: Data Mining
Sponsored Session
Chair: Shuai Huang, University of Washington, Dept. of Industrial
and Systems Eng., Seattle, WA, United States of America,
1 - Social Media Analytics for the Promotion of Mental Health
Qingpeng Zhang, Assistant Professor,
City University of Hong Kong, Kowloon, Hong Kong - PRC,
The digital footprints of Web users left on social media present important mental
health proxies. In this work, we aim to characterize the dynamics of the online
social groups for the mutual help of people suffering from depression. We
identified unique features in both language and social interaction patterns, and
interesting relationship between the two, which could have important
implications of the causes and factors of depression.
2 - Adaptive Cluster-based Oversampling Method: Application to
Gynecological Surgery Failure Prediction
Iman Nekooeimehr, PhD Candidate, University of South Florida,
14304 Wedgewood Ct., Apt. 201, Tampa, FL, 33613, United
States of America, Stuart Hart,
Allison Wyman, Susana Lai-yuen
A new oversampling method called Adaptive Semi-Unsupervised Weighted
Oversampling is presented for imbalanced dataset classification. It is adaptive, and
avoids overgeneralization and overfitting. The method was used with Support
Vector Machines to predict surgical failure after gynecological repair operations.
Results show 76% weighted accuracy and improvement over other oversampling
methods.
3 - Real-time Detection of System Change Points via Graph Theoretic
Sensor Fusion
Prahalad Rao, SUNY Binghamton, 4400 Vestal Pkwy. E,
Binghamton, NY, United States of America,
Chou-An Chou, Samie Tootooni
We propose a novel graph theoretic approach for detection of system change
points from multidimensional sensor data. The approach is based on transform
time series data into an un-weighted and undirected planar graph, and
subsequently extracting topological invariants. This approach outperforms
conventional statistics-based monitoring techniques. We demonstrate the
effectiveness of the approach based on experimentally acquired sensor data from
advanced manufacturing processes and healthcare.
4 - High-throughput Screening for Rule Discovery from High-
dimensional Datasets
Mona Haghighi, University of South Florida, 3202 E Fowler
Avenue, Tampa, FL, 33620, United States of America,
Shuai Huang, Xiaoning Qian,
Bo Zeng
We propose a rule-based methodology to Identify risk-predictive baseline patterns
of Alzheimer’s disease through a network-based mathematical model. We apply
data-mining techniques to reduce dimensionality while taking care of synergistic
interaction of variables. Selecting a set of rules to monitor the progression of the
disease is the second part of this study.
TC32
32-Room 409, Marriott
Decision Support Systems for Data Mining
Contributed Session
Chair: Zhiguo Zhu, Associate Prof., Dongbei University of Finance and
Economics, No. 217 JianShan St., Shahekou District, Dalian, 110625,
China,
1 - A Mixture Method of Multivariate Time Series Clustering
Cheng-Bang Chen, Penn State University, 233 Leonhard
Building, University Park, PA, 16802, United States of America,
Soundar Kumara
Time series clustering is widely used in different domains. Although much
literature is available on time series clustering, only a few articles relate to
multivariate time series clustering. This research developed a clustering
methodology and applies different similarity/dissimilarity measures to
multivariate time series datasets. It can reduce the data size and has good
clustering performance.
TC30