2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
75
2 - Generating And Solving The Large Scale AC-security Constrained
Optimal Power Flow Problems In Parallel
Feng Qiang, Argonne National Laboratory, Lemont, IL, 60439,
United States, , Cosmin G Petra,
Joseph A Huchette, Miles Lubin, Mihai Anitescu
In this talk, we present an integrated approach for the modelling and solution of
the AC-SCOPF problems using StructJuMP, a newly developed parallel extension
of JuMP for modelling large scale optimization problems in Julia and PIPS
optimization solver for HPC platforms. We will present a thorough study of the
the parallel performance of StructJuMP and PIPS for large scale AC-SCOPF
instances on hundreds of nodes.
3 - Paraxpress: A Massively Parallelized MIP Solver Designed To Run
On The Largest Supercomputers
Yuji Shinano, Zuse Institute Berlin, Takustrasse 7, Berlin, 14195,
Germany, , Timo Berthold, Stefan Heinz
The Ubiquity Generator (UG) is a framework for the external parallelization of
MIP solvers. It was used to develop ParaSCIP, a distributed memory, massively
parallel version of the open source solver SCIP, that runs on up to 80,000 cores in
parallel. In this talk, we introduce ParaXpress, for which one of the fastest
commercial MIP solvers, the FICO Xpress-Optimizer, has been parallelized by UG.
Combining the internal shared-memory parallelization of Xpress and the external
parallelization of UG, we aim at a new order of magnitude for supercomputer
core-usage in MIP solving.
SC19
106B-MCC
Computation and Theory in Network Optimization
and Analysis
Sponsored: Computing
Sponsored Session
Chair: Cole Smith, Clemson University, Clemson University, Clemson,
SC, 29634, United States,
1 - Models And Algorithms For Maximum Proportional Flow
Problems With Semicontinuous Restrictions
Robert Mark Curry, Clemson University, Clemson, SC,
United States, , Cole Smith
We consider a variation of the multi-source, multi-sink maximum flow problem
in which flow must emanate from the source nodes according to a prescribed rate,
while flow arrives to the sink nodes at another given rate. Additionally, we
restrict flow variables to be semicontinuous, in which the flow must either be 0 or
no less than some lower bound. We call this problem the semicontinuous
maximum proportional flow problem (SC-MPFP) since the amount of outgoing
flow must leave the source nodes and arrive at the sink nodes according to a
given proportional pattern. To solve the SC-MPFP, we decompose the formulation
and employ a Branch-and-Price algorithm.
2 - Enumeration Algorithms For Infrastructure Resilience Analysis
W Matthew Carlyle, Naval Postgraduate School,
David Alderson
We propose a functional definition of infrastructure resilience based on
parametric analysis of two-stage (attacker-defender) and three-stage (defender-
attacker-defender) models that require enumeration of a potentially enormous
number of optimization problems. We present computational techniques that use
bounding arguments to significantly limit the enumeration while still providing
useful measures of infrastructure resilience and support the use of faster heuristic
algorithms for the most difficult of these problems.
3 - Faster Algorithms For The Time-cost-tradeoff Problem And
Minimum Cost K-flow Problems With A New
All-min-Cuts Procedure
Dorit S. Hochbaum, University of California, Berkeley, Berkeley,
CA, United States,
We explore surprising links between the time-cost-tradeoff (TCT) problem in
project management and the minimum cost flow problem (MCF) leading to faster
algorithms for both problems. The algorithm relies on a new procedure all-min-
cuts procedure, which for a given maximum flow, is capable of generating all
minimum cuts of equal value very efficiently. This results in faster strongly
polynomial algorithms for unit capacity MCF, the K-MCF problem and uniform
costs TCT and match the complexity of the fastest algorithm for the assignment
problem.
SC20
106C-MCC
Novel Dimension Reduction Techniques for High
Dimensional Data Using Information Complexity
Invited: Tutorial
Invited Session
Chair: Hamparsum Bozdogan, University of Tenneesse-Knoxville, Oper
and Mgmt Sci, Knoxville, TN, 37996, United States,
1 - Novel Dimension Reduction Techniques For High Dimensional
Data Using Information Complexity
Hamparsum Bozdogan, University of Tennessee-Knoxville,
Oper and Mgmt Sci, Knoxville, TN, 37996, United States,
, Esra Pamukcu
This tutorial introduces and develops two computationally feasible intelligent
feature extraction techniques that addresses the potentially daunting statistical
and combinatorial problems. First part of the tutorial employs a three-way hybrid
between: Probabilistic Principal Component Analysis (PPCA) to reduce the
dimensionality of the dependent variables; Multivariate regression (MVR) models
that account for misspecification of the distributional assumption to determine a
predictive operating model for glass composition for automobiles; and uses the
genetic algorithm (GA) as the optimizer along with the misspecification-resistant
form of Bozdogan’s ICOMP as the fitness function. Second part of the tutorial is
devoted to dimension reduction via a novel Adaptive Elastic Net (AEN) regression
model to reduce the dimension of a Japanese stock index called TOPIX as the
response to build a best predictive model when we have “large p, small n”
problem. Our results show the remarkable dimension reduction in both of these
real-life examples of wide datasets, which demonstrates the versatility and the
utility of the two proposed novel statistical data modeling techniques.
SC21
107A-MCC
Monitoring and Prevention of Healthcare
Associated Infections
Sponsored: Health Applications
Sponsored Session
Chair: Eduardo Perez, Texas State University, 1, San Marcos, TX, 1,
United States,
1 - Optimal Pooling Strategies For Nucleic Acid Testing Of Donated
Blood Considering Viral Load Growth Curves And Donor
Characteristics
Hadi El-Amine, Virginia Tech, Blacksburg, VA, United States,
, Hadi El-Amine, George Mason University, Fairfax,
VA, 22030, United States, , Ebru Korular Bish,
Douglas R Bish
Blood product safety, in terms of being free of transfusion-transmittable infections
(TTIs), is crucial. Nucleic Acid Testing (NAT) technology enables earlier detection
of infections but is more expensive, hence, most blood centers administer NAT to
pools of blood samples from multiple donors. Since some donor characteristics are
uncertain, we develop a chance-constrained model that determines the optimal
NAT pool sizes for various TTIs, considering both non-universal (where first-time
donors undergo more extensive screening), and universal (i.e., common testing
for all donors) strategies, so as to minimize the TTI risk, while remaining within
the testing budget with a high probability.
2 - Infection Control In Outpatient Clinics:
The Risk- Efficiency Tradeoff
Cory Stasko, Massachusetts Institute of Technology,
,
As HAIs remain a major problem and U.S. healthcare shifts towards outpatient,
understanding the risk of HAIs in this environment is important. For a particular
clinic, we simulate the potential impacts of two interventions: 1) improving hand
hygiene, and 2) separating likely infectious patients from other patients. By
creating an integrated discrete event and agent based model to simulate patient
flow and the spread of infections, we examine how these two domains interact,
testing 891 intervention combinations in terms of wait time, infection exposures,
and implementability. Interdependent effects and the tradeoff between risk
reduction and operational efficiency are discussed.
SC21