2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Disruption Management For Outbound Baggage Handling With
Worker Assignment
Christian Ruf, TU Muenchen, Arcisstr. 33, Munich, 80333,
Germany,
Outbound baggage is transferred to departing airplanes. Flights have to be
assigned to handling facilities, the handling has to be scheduled and workers have
to be staffed to the flights. We propose a model and a solution procedure to plan
the outbound baggage handling rolling planning fashion which allows for
considering disruptions and updates of problem parameters at each decision
epoch. In a computational study we show that the procedure is capable of giving
a good solution in a reasonable amount of time even under severe disruptions.
3 - Demand Learning And Agreement Delay In Technology Adoption
Wei Zhang, University of Hong Kong, Pokfulam Road, Hong Kong,
China,
Delay of price agreement is common when new technologies are being adopted.
Existing theories attribute agreement delay in bilateral negotiations to either
asymmetric information or behavioral constraints. We discover that incentives to
learn about the uncertain demand drive delay of agreements, even when
information is symmetric. Contrary to most existing theories, costly delay can
benefit both negotiators.
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Legends B- Omni
Optimization Methodology I
Contributed Session
Chair: Abdulaziz Saud Alkabaa, Ph.D. Candidate, University of
Tennesee, 1001 Cain Oak Place, Apt 1001, Knoxville, TN, 37909,
United States,
1 - Constraint Programming Models For The Irregular Cutting And
Packing Problems
Luiz Henrique Cherri, University of São Paulo, São Carlos,
13566-590, Brazil, ,
Maria Antonia Carravilla, Cristina Ribeiro, Franklina M Toledo
We propose new constraint programming models for variants of the two-
dimensional irregular cutting and packing problem. In the literature, several
heuristics were proposed for some problem variants, however there is no exact
method or mathematical model for many of them. Using the constraint
programming models we can represent and solve the irregular cutting and
packing variants by exact methods. Since the enforcement of the no overlap
among the pieces are the core constraints of all the problem variants, the
formulations are built around this basis.
2 - An Iterative Method For Biobjective Mixed Integer Linear
Programming Models
Hadi Farhangi, Research Assistant, Missouri University of Science
and Technology, 1870 Miner Circle, 236, Engineering Mgmt &
Systems Eng, Rolla, MO, 65409, United States, ,
Dincer Konur
In this study, we propose an iterative method to generate the complete set of
Pareto efficient solutions for biobjective mixed integer linear programming
models. The Pareto efficient set is obtained by sequentially solving mixed integer
linear programming models and utilizing the properties of the feasible search
space. A numerical study demonstrates the performance of the solution method.
3 - Ensuring Scalability And Re-Usability Of Spreadsheet Analytical
And Optimization Models
Larry J LeBlanc, Professor, Vanderbilt University, Owen Graduate
School of Mgmt, 401 21st Ave South, Nashville, TN, 37203, United
States, , Thomas A Grossman
Spreadsheet optimization models are harder than their algebraic counterparts to
scale up and down in size. We show how to overcome this spreadsheet scalability
disadvantage—We show how to program an optimization model in a spreadsheet
that can easily be scaled up or down in size and re-optimized using the Excel
Solver as easily as algebraic models. We give examples involving supply chain
optimization.
4 - A Novel Branching Rule For Branch And Bound Based on
Mahalanobis Distance
Abdulaziz Saud Alkabaa, PhD Candidate, University of Tennesee,
1001 Cain Oak Place, Apt 1001, Knoxville, TN, 37909,
United States, Alberto Garcia-Diaz
The critical rules affecting the Branch-and-Bound (B&B) algorithm’s solution
performances are mostly regarded to the selection strategies of the search trees’
variables and nodes. These strategies can significantly impact on the algorithms’
efficiency. The available branching strategies in the literature, however, are not
reliable in large problems (Linear Integer problems). In this research, we propose
a novel branching strategy that is based on the concept of Mahalanobis Distance.
Our analytical and numerical results show that the purposed strategy can
effectively improve the B&B solution performances and works capably in a range
of problem sizes.
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Legends C- Omni
Behavioral Operations I
Contributed Session
Chair: Nazaré Rego, Escola de Economia e Gestão, Universidade do
Minho, Braga, Portugal,
1 - Study Of Patient Satisfaction Perception Based On Medical
Experience And Health Cognition
Jianjie Zhang, Beijing Institute of Technology, Beijing, China,
, Jinlin LI, Rong Zhang, Jian Xue
This paper examines patient experience and health cognition in outpatient from
nine cities of conducting discrete choice experiments,we identify
discrepant patients in several attributes and the individual-difference about the
health cognition that can explain such discrepancy.For the high degree of the
health cognition patients,medical environment and waiting time affection is not
significant.however,for the low degree of group,both two attributes affect
addition to providing the empirical description in China’s
healthcare market,our study offers patient behavioral optimization suggestions to
improve patient satisfaction perception.
2 - Detecting Market Irrationality Using News Sentiment
Transfer Entropy
Anqi Liu, PhD Candidate, Stevens Institute of Technology,
Hoboken, NJ, 07030, United States,
Steve Y Yang
Studies in behavioral finance have shown that investors are not rational, and
market sentiment and returns have complex interactions. In this study we
explore the non-linear relationship between news sentiment and market returns
according to the transfer entropy statistic which identifies the amount of
directional information flow. We identify two market regimes: sentiment
dominance and market dominance. Further analysis suggests that the sentiment
dominance indicates more irrational market activities contributing to elevated
mispricing and high volatility, while market dominance reflects informational
market efficiency.
3 - The Dark Side Of The Singularity: Can OR/MS Help?
John D C Little, Institute Professor, Massachusetts Institute of
Technology, M.I.T. Sloan School Of Management, Room E62-534,
Cambridge, MA, 02142, United States,
The “Singularity” is the point in time when artificial intelligence (AI) exceeds
human intelligence. This may occur by putting AI on computers, by biological
creation, or by a mixture of both. Some of the people writing about this or
developing advanced AI are Victor Vinge, Ray Kurzweil (the Singularity is Near),
Tom Malone, Ben Goertzel and Hugo de Garis. The dark side is that most people
in this room will be left far behind. Kurzweil notes that AI develops
exponentially, whereas most of us extrapolate linearly.
4 - Performance Effects Of Diversity Of Experience In Fluid Teams
Antti Tenhiala, IE Business School, Madrid, Spain,
, Constantin Alba, Fabrizio Salvador
Analyzing fluid teams in a software services setting, we study the performance
effects of diversity of experience, partitioning the diversity construct into three
dimensions: segmentation, disparity, and variety. We also explore how project
complexity moderates the performance effect of each diversity dimension. The
results show that depending on the dimension, diversity of experience may have
either negative, positive, or inverted-U relationship with team performance and
that project complexity may make the effect either more beneficial or more
detrimental.
5 - A System Dynamics Analysis Of Cautious Materials Management
In Hospitals
Nazaré Rego, Escola de Economia e Gestão, Universidade do
Minho, Braga, Portugal,
Nazaré Rego, INESC TEC, Faculdade de Engenharia, Universidade
do Porto, Porto, Portugal, João Claro,
Jorge Pinho de Sousa
The supply system of a hospital provides a wide variety of services and products
through a network composed of central departments and relatively autonomous
wards. This system has to assure a high service level, particularly at critical wards.
In this context, a just-in-case approach to inventory control has been frequently
observed and, when the inventory at the DC is insufficient to meet all requests,
priority in its allocation may be given to critical wards. We use System Dynamics
to analyze the effect of these practices on inventory levels and related service
level of a hospital supply system. Our results indicate that they may have a
negative impact on the desired materials management outcomes.
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