2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
175
Monday, 12:30PM - 2:30PM
Poster Session
Exhibit Hall
Monday Poster
Poster Session
Mature Oil Fields And Real Options Valuation: Simulation In The
Brazilian Oil Industry
Carlos Abreu, Adjunct Professor, Federal University of Rio Grande
do Norte State (UFRN), Avenida das Brancas Dunas, Natal,
59064720, Brazil,
Real Option Valuation in the Oil industry is an important tool for decision-making
valuating a potential flexibility caused by the uncertainties in oil projects. Mature
fields are a considerable portion of producing oil fields around the world. These
oil fields production projects need positive future expectations regarding oil prices
to get a positive investing decision. The Real Options models valuates the decision
to wait for better expectation in prices. In this paper we have a Real Options
analysis in two simulations for mature oil field in the northeastern of Brazil
applying a decision-making rule using Real Options Valuation, net present value
and return on investment indicator.
Class-based Warehouse Location Allocation For Textile Products
Esra Agca Aktunc, Kadir Has University, Faculty of Engineering
and Natural Sciences, Kadir Has Caddesi Cibali, Istanbul, 34083,
Turkey, Halil Argun, Erkin Gokce
This study focuses on building a layout plan by allocating storage space to
products in a warehouse of a textile company (English Home) which allows for
the minimum total travel distance of operators for order picking or placing. The
study is carried out by (1) performing regression analysis for sales forecasting for
each product class, (2) applying Analytical Hierarchy Process for determining
product class weights, and (3) formulating and solving a linear program to
minimize the weighted total distance between storage locations, collecting area,
and loading dock using GAMS. Optimal solution results in 26.8% less distance
required for order picking than the previous layout.
Application Of Advanced Analytics In Banking Big Data
Mou Dutta, Genpact Analytics & Reserach, Danbury, CT,
Data is meaningful when it delivers insights. Data analysis is smart when insights
are actionable. In today’s world big data and analytics is transforming the business
end to end with smart intelligent insights challenging the conventional thought
process and enabling the marketers to optimize strategies to build a genuine
customer connect and cultivate a positive relationship. This presentation aims to
highlight how marketers are shifting their attention to the application of cutting
edge advanced analytics solutions to gain in-depth knowledge of consumer
buying preferences and product affinity and hence optimize existing cross selling
and up selling marketing strategies.
Efficient Algorithm To Improve Scheduling Problem Solutions
Golshan Madraki, Ohio University, Athens, OH,
Any choice-free manufacturing system can be represented by a directed acyclic
graph (DAG) where the nodes and edges represent the operations, the sequence
of the operations, and with the scheduling of the jobs respectively. Graphical wise,
perturbation may occur over structure of the graph denoting scheduling or
sequencing of operations. The goal of current research is to find the efficient
algorithms to calculate changes to the makespan in a system under multiple
structural perturbations. The paper will show that there will be savings in the
complexity of the calculations if the perturbations are not extensive. As an
example, a buffered job shop system is considered.
Comparing Two Goods-to-person Order Picking Systems For
Online Retailing
Francisco Jose Aldarondo, University of Michigan, Ann Arbor, MI,
Using simulation modeling and an on-line retail setting, we compare the
performance of two types of goods-to-person order picking (OP) systems, namely,
the Kiva system and the Miniload-AS/RS with a conveyor loop (to connect the
pick stations). The two systems are compared on the basis of quantitative factors
such as expected throughput (line items picked per hour), expected picker and
material handling equipment utilizations, and order completion times. We also
compare the two systems in terms of qualitative factors that are relevant for OP
systems.
Two-dimensional Cutting Problem And Pallet Loading Problem
Using Industrial Robots
David Alvarez Martinez, Los Andes University, Colombia, Bogotá,
Colombia; , Guillermo A. Camacho
Muñoz
We developed an automatic cutting and palletizing system, solving the two-
dimensional single knapsack problem and the distributor’s pallet loading problem.
The system is composed by: optimization stage, code-generator, manipulator and
plasma cutter (vacuum gripper). At the optimization we use a GRASP algorithm;
at the code generation we use the forward kinematic model (FKM) of the
manipulator. The GRASP was validated by using the classical benchmarks. The
FKM was validated using the simulator and the controller provided by the Robot
vendor. Finally, we enhanced the cutting procedure through a post-processing. It
reduces the time and keeps the accuracy, but increases particulate generation.
Meaningful Use Of Health Information Technology And Process
Quality Of Care At Hospitals: A Patient Safety Culture Perspective
Ajit Appari, University of Texas Health Science Center at Houston,
1200 Pressler Street, RAS W-310, School of Public Health,
Houston, TX, 77030, United States,
Xin (David) Ding, Rajendar R Aparasu
Based on the Resource Based View and Sociotechnical System Theory, we
examined the synergetic effect of meaningful use of health information
technology (IT) and patient safety culture on hospital quality of care performance.
Hospital safety culture was measured using composite score derived from
confirmatory factor analysis. Health IT meaningful use was measured as
composite index of nine meaningful use criteria with patient days as weights. We
analyzed data from 305 nonfederal acute care hospitals using two-step Heckman
estimation approach and adjusting for autocorrelation in performance outcomes.
Our results show empirical support for the hypothesized relationship.
Gait Assessment: Correlation Of Gait Parameters With Falls
Among Patients With Cognitive Impairment
Idil Arsik, Georgia Institute of Technology, 765 Ferst Drive,
Atlanta, GA, 30332, United States,
Pinar Keskinocak, Joe Nocera, Gregory J Esper
In aging, alteration in the customarily stable gait pattern is one of the most
consistent predictors of falls. Adults with cognitive impairment fall 5x more than
their cognitive intact peers. In this study, we assess the correlation between gait
characteristics captured by gait mat technology and history of falls among patients
with Mild Cognitive Impairment and Alzheimer’s Disease diagnoses.
On Optimization Of Carbon Capture, Utilization, And Storage
Supply Chains Under Uncertainty
Mahnaz Asghari Khankandi, Virginia Tech, Blacksburg, VA, 24060,
United States,
Carbon capture, utilization, and storage (CCUS) is a crucial technology to mitigate
climate change. Due to the high costs of the technology, a great deal of attention
has been focused on how the captured Co2 can be optimally utilized or stored.
We study optimizing CCUS supply chains under an uncertain environment. In
this poster, we present an algorithm to generate a candidate network for Co2
transportation and a model for optimizing the utilization and storage of the
captured Co2 in CCUS systems.
Ethanol Risk Management Modeling
Iddrisu Awudu, Quinnipiac University, 12 Kaye Plaza, Apt E-22,
Hamden, CT, 06514, United States,
A theoretical model is developed including margins and risk is measured using
value at risk (VaR). An empirical model is developed and extended to VaR using
copulas to analyze the marginal distribution and dependence structure for input
and output prices on margins. Efficient frontier curves analyzing VaR with and
without copula are discussed. The results compare varying risk-strategy measures
for long corn, short corn, and combining short and long corn. Sensitivity analyses
are conducted for functional changes in the margin as a result of ethanol price
changes.
A Location Allocation Model For Facility Planning To Minimize
The Operational Cost
Damitha Bandara, Dr., Albany State University, 2805, Albany, GA,
31721, United States,
Locating and allocating distribution centers optimally is a crucial and systematic
task for decision-makers. Optimally located distribution centers can significantly
improve the logistics system’s efficiency and reduce its operational costs. In this
research, we develop a mathematical model to determine the optimal locations
and allocations for distribution centers that minimizes the operational cost. The
model is used to find the optimal location and allocation of distributions centers
for a leading company in the USA. Computational results show that the company
can reduce their operational cost significantly by implementing new optimal
distribution locations.
POSTER SESSION