Informs 2015

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INFORMS Philadelphia – 2015
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2 - Transportation Optimizer System as Applied to Rail Car
Assignment Problem
Ilya Buzytsky, BIAS Intelligence, 7741 37th Ave NE, Seattle, WA,
98115, United States of America,
BIAS Optimizer System was developed to address problems frequently
encountered in many transportation and distribution logistics applications. Its
objective is to find optimal solution to problems that can be formulated in terms
of supply/cost/demand configuration across large matrix representing a multi-
node network: The solution helps find an assignment that would meet the
demand supported by available supply across all nodes and satisfy all business
rules and constraints at the minimum cost.
3 - Diet Problem Pevisited
Fariborz Partovi, Professor, Drexel University, 33rd Chestnut
Street, Department of Decision Sciences, Philadlphia, PA, 19003,
United States of America,
It has been close to seventy years since the Diet problem was introduced by
Stigler (Stigler 1945). However the problem with the classical Diet models is
based on lack of proper presentation of food preferences. For many people,
especially when they are eating outside their home, the content of the food as far
as nutrition is concern may be not as important as the taste of the food. In this
article we modify Diet problem using extensions of linear programming to
consider the above issues
WE19
19-Franklin 9, Marriott
Computational Optimization with Risk and
Uncertainty
Sponsor: Computing Society
Sponsored Session
Chair: John Siirola, Sandia National Laboratories, P.O. Box 5800,
MS 1326, Albuquerque, NM, 87185-1326, United States of America,
1 - Multistage Power Generation Capacity Expansion Models with
Different Risk Measures
Shu Tu, Lehigh University, H.S. Mohler Laboratory, 200 West
Packer, Bethlehem, PA, 18015, United States of America,
, Boris Defourny
We investigate different stochastic optimization formulations for the multistage
power generation capacity expansion problem. In particular, we focus on risk
measures whose parameters can be calibrated from market data.
2 - Exploiting Inter-scenario Information to Acclerate
Progressive Hedging
John Siirola, Sandia National Laboratories, P.O. Box 5800, MS
1326, Albuquerque, NM, 87185-1326, United States of America,
Jean-paul Watson, David Woodruff
Progressive Hedging (PH) is a scalable and effective approach for solving large
stochastic programming problems through scenario-based decomposition.
However, PH is sensitive to key tuning parameters (notably rho) and for many
problems can exhibit slow convergence. In this work we present new approaches
for accelerating convergence and improved tuning by propagating key
information among scenarios.
3 - Production Planning under Uncertainty and Service
Level Constraints
Suleyman Karabuk, Associate Professor, University of Oklahoma,
School of Industrial and Sys Engineering, 202 W. Boyd St.,
Room 124, Norman, OK, 73019, United States of America,
Consider a production planning problem with machine changeover and inventory
carrying costs, and service level constraints, where demand for products is
probabilistic. We formulate the problem as a multistage stochastic programming
model with recourse. The resulting model is very large scale even for trivially
small size instances. We develop an effective decomposition algorithm where
individual product sub problems are solved by a novel probabilistic dynamic
programming model.
WE21
21-Franklin 11, Marriott
Mathematical Modeling of HIV at the Cellular,
Individual, and Population Level
Sponsor: Health Applications
Sponsored Session
Chair: Eva Enns, Assistant Professor, Univeristy of Minnesota, 420
Delaware St. SE, Minneapolis, MN, 55408, United States of America,
1 - Mathematical Modeling of HIV Viral Dynamics and Immune
Response During Treatment Interruptions
Nargesalsadat Dorratoltaj, Virginia Tech, Room 392, Vet Med
Phase II., Blacksburg, VA, 24060, United States of America,
, Josep Bassaganya-riera, Stanca Ciupe,
Stephen Eubank, Margaret O’dell, Hazhir Rahmandad,
Kaja Abbas
The objective of this study is to understand and predict HIV viral and immune
dynamics at the individual level during treatment interruption and low adherence
in developing AIDS. We use ordinary differential equations to build immune-viral
dynamics of HIV/AIDS during treatment interruption. The results of the
simulation show that the time that patients start treatment and for how long they
stay on treatment before interruption are unique predictor for time to progress to
AIDS.
2 - A Data-driven Approach to Understanding HIV Care Trajectories
and Retention in Care Challenges
Eva Enns, Assistant Professor, Univeristy of Minnesota,
420 Delaware St. SE, Minneapolis, MN, 55408,
United States of America,
Sub-optimal retention in HIV primary care is associated with increased risks of
mortality, detectable viral loads, and other complications compared to regular,
ongoing care; however, the standard dichotomous measures of retention (e.g.,
in/out of care) ignore the diversity and complexity of individual care trajectories.
In this talk, I describe a data-driven approach to understanding HIV care patterns
and how to incorporate complex care behaviors into mathematical models of HIV
interventions.
3 - Modeling a Bi-layer Contact Network of Injection Drug Users and
The Spread of Blood-borne Infections
Rui Fu, Stanford University, 74 Barnes CT, Stanford, CA, 94305,
United States of America, Alexander
Gutfraind, Margaret L. Brandeau
Blood-borne infections can spread among injection drug users (IDUs) via risky
sexual and needle-sharing contacts. To accurately model the spread of such
contagions among IDUs, we build a bi-layer network that captures both types of
risky contacts. We present methodology for inferring important model
parameters. Such a model can be used to evaluate the efficacy of various
programs that aim to combat drug addiction and contain blood-borne diseases
among IDUs.
4 - Measuring the Potential Impact of Combination Prevention in
Sub-Saharan Africa
Amin Khademi, Assistant Professor, Clemson University, 130-D
Freeman Hall, Clemson, SC, 29634, United States of America,
Sunanth Anand
A public health approach to combination HIV prevention is advocated to contain
the epidemic in Sub-Saharan Africa. We explore the implications of universal
access to treatment along with HIV education scale-up in the region. We develop
an HIV transmission model, calibrate it with data from South Africa and simulate
the impacts of universal access to treatment along with HIV education scale-up on
HIV trends.
WE21