2016 INFORMS Annual Meeting Program

294 / 561

INFORMS Nashville – 2016
294
Taxi Sharing
Mustafa Lokhandwala, Purdue University, 241 Sheetz Street,
Apt 14, West Lafayette, IN, 47906, United States,
New York City has one of the busiest transportation systems in the world. This
study focuses on a part of this network i.e. taxis and attempts to analyze the
benefit of Taxi Sharing using simulation software and optimization techniques.
The focus of our study will be to build an agent-based simulation model using trip
data obtained from the New York Taxi and Limousine Commission, model the
decision making methodologies of the agents in a taxi sharing scenario and run
this model using the most recent trip data within New York City. The result from
this experiment will be to optimize the number of taxis operating on the streets of
New York City and also quantify the economic and environmental benefits of the
same.
Acceleration Of A Communication Efficient Distributed Dual Block
Descent Algorithm
Chenxin Ma, Lehigh University, 200 West Packer Avenue,
Bethelehem, PA, 08801, United States,
Distributed optimization algorithms for very large-scale machine learning suffer
from communication bottlenecks. Confronting this issue, a communication-
efficient primal-dual coordinate ascent framework (CoCoA) and its improved
variant CoCoA+ have been proposed, achieving a convergence rate of O(1/t) for
solving empirical risk minimization problems with Lipschitz losses. In this paper,
we propose an accelerated variant of CoCoA+ and show that it has a rate of
O(1/t2) in terms of reducing dual suboptimality. Our analysis is also notable in
that our convergence rate bounds involve constants that, except in extreme cases,
are significantly reduced.
Enhancing Operational Performance Of Emergency Room Team
Maryam M Mahdikhani, PhD Candidate, Rutgers University, 1
Washington Park, Room 1019C, Newark, NJ, 07102, United States,
The study investigates the effect of situational awareness concepts on the
operational performance of involved agents at emergency rooms to increase the
efficiency of performance. Applying ABM techniques makes contributions to
illustrate that the effect of which attributes for which agent is more significant
than others. We considered three main agents by developing their attributions
and variables through random function. Furthermore, situational awareness is
described by availability of authority in case of problems, supervisor feedback, and
resource availability.
An Integrated Black Topsis And Grey Linear Programming
Approach To Deal With Uncertainty And Confidence Level Of
Decision Makers
Hanif Malekpoor, PhD Student, University of East Anglia, Norwich
Research Park, Norwich, NR4 7TJ, United Kingdom,
In order to deal with uncertainty of Decision Makers (DMs) opinions in supplier
selection, applying interval valued data is a popular method. However the level of
confidence, DMs have about their judgments, is also significant. In addition the
supplier’s information related to constraints of order allocation problem is not
always trustable and precise. In this research to overcome the two
aforementioned problems we have developed an integrated approach for order
allocation, using Black-TOPSIS (TOPSIS with interval numbers which their upper
and lower bounds are also grey numbers) and multi objective grey linear
programing to determine the best supplier and order quantity from each
suppliers.
Development Of A Least-cost Diet For The Crew Of A Brazilian
Navy’s Warship
Ernesto Rademaker Martins, Commander, Brazilian Navy, Arsenal
da Marinha no Rio de Janeiro (AMRJ), Rua da Ponte S/N, Ilha da
Cobras, Centro, Rio de Janeiro, 20091000, Brazil,
Marcos Santos, Jessica Alves Souza,
Fabrício Costa Dias, Marcone Freitas Reis
Develop an analytical model for the meals served to the crew of Brazilian Navy’s
warship. Such a diet should take into account the nutritional needs of adult men
aged 18-45 years, as well as the specifics of the work activities performed aboard a
warship. Due to its deterministic nature, sought a solution to the problem in the
light of linear programming, specifically the Simplex Method. The analytical
model was established by the data obtained in the Brazilian Navy’s normative
legislation. The solution of the mathematical model in screen can support the
decision of the management of the military organization, to contribute to the
fulfillment of the Brazilian’s Law.
Modeling Strategic Decisions In Football
Christopher G McCord, Massachusetts Institute of Technology,
Cambridge, MA, United States,
Football has long been recognized as one of the most strategically advanced
professional sports in the US. A team must continually take into account many
different factors when making decisions. In this work, I present a probabilistic
model for the decisions an NFL team may face during the course of the game. I
then present the strategy that maximizes the team’s probability of winning in
various situations, as well as a measure of uncertainty for each decision. Finally, I
compare the model’s optimal decisions with the observed strategies of NFL teams
and hypothesize why coaches behave sub-optimally in many situations.
A Novel Distributed Coordinated Approach For Real-time
Signal Control
Mehrzad Mehrabipour, Graduate Research Assistant, Washington
State University, 1630 NE valley Rd, Pullman, WA, 99164,
United States, Ali Hajbabaie
This study develops a distributed-coordinated methodology for traffic signal
timing optimization problem. Our formulation and solution methodology
distribute the network level signal timing optimization problem to intersection
level. We formulated a mathematical programing model for each intersection,
based on the cell transmission model and created coordination between them to
avoid finding locally optimal solutions. The neighboring intersections coordinate
their decisions to avoid long queues. We also proposed a rolling horizon solution
algorithm and applied it to several case study networks under various demand
patterns and observed very promising results.
Optimal Parking Utilization Management Under
Uncertain Demand
Amir Mirheli, Washington State University, 405 Spokane Street,
Sloan 242, Pullman, WA, 99163, United States,
, Leila Hajibabai
Excessive cruising to find parking spots contributes to additional delays and
imposes indirect costs, safety, and health concerns, particularly in congested
urban areas with limited parking capacity. This research develops a bi-level
stochastic dynamic parking management model under uncertain demand to
simultaneously minimize total costs due to drivers’ decisions, maximize parking
agency’s revenue, and push parking utilization towards a target occupancy. The
problem is solved using a hybrid technique including an approximate dynamic
programming with an embedded single-level conversion. Numerical experiments
show the performance of the proposed algorithm and draw managerial insights.
Regularized Discriminant Analysis For Multisensory Damage
Detection And Decision Fusion Using Lamb-waves
Spandan Mishra, Florida State University, 2005 Levy Avenue,
Tallahassee, FL, 32310, United States, ,
Arda Vanli, Fred Huffer
We have propose a for damage detection which does not require an intermediate
feature extraction step and therefore more efficient in handling data with high-
dimensionality. A robust discriminant model is obtained by shrinking of the
covariance matrix to a diagonal matrix and thresholding redundant predictors
without hurting the predictive power of the model. The shrinking and threshold
parameters of the discriminant function are estimated to minimize the
classification error. Furthermore, bayesian decision-fusion formulation is used to
improve the damage classification obtained from the regularized linear
discriminant analysis approach
Identification Of Optimal Partition For Semidefinite Optimization
Ali Mohammad Nezhad, PhD Candidate, Lehigh University, 200
West Packer Ave, Mohler lab, Bethlehem, PA, 18015, United
States,
The concept of optimal partition was originally introduced for linear optimization
and linear complementary problems and subsequently extended to semidefinite
optimization. For linear optimization and sufficient linear complementary
problems, the optimal partition and a maximally complementary optimal solution
can be identified in strongly polynomial time. In this paper, under no assumption
on strict complementarity, we formalize the optimal partition concept for
semidefinite optimization and present a methodology for an $\epsilon$-feasible
maximally complementary solution.
Should We Decrease Corn Subsidies And Subsidize Fruits
& Vegetables?
Philip F. Musa, Associate Professor and Programs Director,
University of Alabama-Birmingham, PO Box 55544, Birmingham,
AL, 35255, United States,
This Poster calls for programmed reductions of Corn Subsidies with a
corresponding ramping up of Subsidies for fruits and vegetables. If implemented,
this Public Health initiative could have a dramatic positive impact on Obesity
reduction, its associated comorbidities, and healthcare costs in the USA. It should
also enhance Quality of Lives.
Endogenous Time Preference And Exhaustible Resource Use
Makiko Nagaya, Showa Women’ University, Tokyo, Japan,
This paper re-examine a classical topic of exhaustible resource use on the basis of
recent developments in time preference models. We analyze the effects of
endogenous time preference on dynamic properties of resource use, contrasting to
classical Hotelling’s results. Finally, we introduced a concept of minimum required
level of consumption.
POSTER SESSION