Informs 2015

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INFORMS Philadelphia – 2015
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4 - Integrated Variable Importance Assessment in Multi-stage
Manufacturing Processes
Gianluca Gazzola, Rutgers Center for Operations Research,
100 Rockafeller Road, Piscataway, NJ, 08854, United States of
America, , Jeongsub Choi,
Myong K (MK) Jeong, Byunghoon Kim
We introduce a method for the assessment of variable importance in
manufacturing processes characterized by a hierarchy of technical relationships
between stage variables. Regression models of direct technical relationships and a
novel permutation measure are employed to quantify the local contribution of
every variable. Global contributions are finally obtained by integrating these local
assessments, based on the overall structure of indirect and direct technical
relationships in the process.
TA19
19-Franklin 9, Marriott
Computational Integer Optimization
Sponsor: Computing Society
Sponsored Session
Chair: Yan Xu, Director, SAS, 100 SAS Campus Dr., Cary, NC,
United States of America,
1 - Recent Advances in the FICO Xpress MIP Solver
Michael Perregaard, Xpress Team, FICO, International Square,
Starley Way, Birmingham, B37 7GN, United Kingdom,
We will present some of the recent MIP advances in the FICO Xpress solver, with
an emphasis on how it is able to exploit the ever increasing core counts of
modern CPUs.
2 - The SAS MILP Solver: Current Status and Future Developments
Philipp Christophel, SAS Institute Inc., 100 SAS Campus Dr.,
Cary, NC, 27607, United States of America,
Menal Guzelsoy, Imre Polik,
Amar Narisetty
We give an overview of the current status of the SAS mixed integer linear
programming (MILP) solver that is part of the SAS/OR product. The focus will be
on describing recent implementation efforts for the MILP presolver as well as
future development directions.
3 - Performance Improvements and New Features in the
Gurobi Optimizer
Chris Maes, Senior Developer, Gurobi Optimization, Inc., 125
Beacon St, Apt. #4, Boston, MA, 02116, United States of America,
This talk will cover the latest developments in the Gurobi Optimizer. We’ll discuss
the new Gurobi Cloud, which makes it easy to launch one or more Gurobi
machines when you need them. We’ll also talk about our upcoming release,
which includes significant performance enhancements and several new features.
4 - CPLEX Keeps Getting Better
Andrea Tramontani, CPLEX Optimization, IBM Italy, Via Martin
Luther King 38/2, Bologna, Italy,
We present some of the new features and algorithmic techniques that have been
recently added to IBM ILOG CPLEX Optimizer, and we give detailed benchmark
results that demonstrate the performance improvements achieved in latest CPLEX
versions.
TA20
20-Franklin 10, Marriott
Cloud Services and Applications
Cluster: Cloud Computing
Invited Session
Chair: Grace Lin, Data Analytic Technology and Applications (DATA),
Data Analytic Technology and Applications (DATA), Taipei, Taiwan -
ROC,
1 - Revealing Power Structures through Novel
Biclustering Approaches
Sabine Baumann, Professor Dr., Jade University, College of
Mgmt, Info., Tech., Friedrich-Paffrath-Str. 101, Wilhelmshaven,
22880, Germany, , Oliver Eulenstein,
Christoph Wunck
Cloud and big data provide unprecedented access to massive interaction networks
of people and organizations. However, exploring such rich data environments
encounters equally extensive challenges: unreliable, incomplete or distorted
information, or computational limitations. We recover missing interactions from
vast corporate networks using novel biclique clustering techniques to detect the
most significant edges, and hence provide new insights into power structures.
2 - Running Your Optimization Model on the Cloud with the IBM
CPLEX Studio IDE
Frederic Delhoume, Software Engineer, IBM, 9 Rue de Verdun,
Gentilly, 94253, France,
We will show how to easily run optimization models from the IBM CPLEX Studio
IDE. We will also demonstrate how to monitor the cloud service and get local
results from the remote optimization service. A REST API way of running models
on the cloud will be shown.
TA21
21-Franklin 11, Marriott
Medical Decision Making in Cancer Care
Sponsor: Health Applications
Sponsored Session
Chair: Christine Barnett, University of Michigan, 1205 Beal Ave.,
Ann Arbor, MI, United States of America,
1 - Predictive Modeling for Optimal Design of Cancer
Detection Protocols
Selin Merdan, University of Michigan, 1205 Beal Avenue,
Ann Arbor, MI, 48109, United States of America,
Brian Denton
Diagnosis of chronic diseases often involves expensive and invasive tests and
procedures. Predictive models can play an important role in determining the
optimal diagnostic protocol based on individual patient risk factors. We discuss an
approach for developing predictive models using clinical observational data that
suffers from common sources of bias such as low disease prevalence and missing
data. We illustrate the use of these models for optimization of prostate cancer
diagnostic protocols.
2 - Model-based Calibration for Natural History Modeling
Jing Voon Chen, University of Southern California, Epstein Dept
of Indus & Sys Eng, Los Angeles, CA, United States of America,
, Julie Higle
A natural history (NH) model often requires calibration of unobservable model
parameters to fit observed data. Uncertainty in the data and in the calibrated
parameters impacts confidence in the optimal decision. We propose a method for
model-based calibration that is resilient to these uncertainties, especially for
comparative analyses of disease screening or treatment strategies. Illustrative
examples and sensitivity analyses will be discussed.
3 - Assessment of Individualized Human Papillomavirus (HPV)
Vaccination Strategies
Fan Wang, University of Arkansas, 4207 Bell Engineering Center,
Fayetteville, AR, United States of America,
, Shengfan Zhang
The human papillomavirus (HPV) is the most common sexually transmitted virus
in the U.S. To prevent multiple cancers attributable to the HPV, HPV vaccine is
recommended for preteens and teens who have not been exposed to HPV. We
develop a simulation model for the optimal design of personalized HPV
vaccination program, which incorporates multiple social-behavioral and
demographic risk factors. The efficacy of the HPV vaccination program is
evaluated in terms of the HPV-related health outcomes.
4 - Tailoring CRC Screening Strategy for Different Age- and
Gender-specific Population Subgroups
Carolina Vivas, Purdue University, West Lafayette, IN 47906,
United States of America, , Nan Kong, Robert
Klein, Thomas Imperiale
Standard guidelines for colorectal cancer (CRC) strategies do not consider
different age- and gender-specific subgroups for tailored screening
recommendations. Recent evidence suggests that men tend to face a higher risk of
developing advance adenomas earlier than women. We apply Design of
Experiments techniques to quantify the risk differences on CRC disease
progression. Model based cost-effectiveness analyses of various screening
strategies are conducted for different population subgroups.
TA19