2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Modeling Medical Overpayments Using Truncated Distributions
Babak Zafari, Babson College, Babson, MA, United States,
In this work, we explore some new methods used in overpayment extrapolations
and compare their performance to existing models.
3 - Procurement Models For Clinical Supplies: Indian Context
Bhavin J Shah, Associate Professor, Indian Institute of
Management, Indore, Faculty Office # C-206, First Floor,,
Prabandh Shikhar, Rau-Pithampur Road,, Indore - Madhya
Pradesh, 453556, India, , Hasmukh Gajjar
This paper seeks to understand and explore applications of procurement models
followed in sourcing clinical supplies to reduce cost of healthcare in Indian
hospitals. It aims at improving efficiency of healthcare delivery without sacrificing
service levels and explore various alternatives such as forming cross-functional
collaborative teams comprising clinicians and sourcing experts for operational
improvements.
4 - A Multiple Criteria Decision Tree Algorithm For Selecting Breast
Cancer Treatment
Mostafa Hasan, Research Assistant, Wichita State University,
1629 N Fairmount St, Wichita, KS, 67208, United States,
, Esra Buyuktahtakin, Elshami Elamin
According to the American Cancer Society, 246,660 new cases will be diagnosed
with invasive breast cancer and approximately 40,450 women will die in the
United States in 2016. To deal with the complexity, a decision support system is
proposed combining MCDM techniques and decision trees. We then propose a
detailed algorithm which will evaluate each factor and condition of the breast
cancer patients in order to determine the best treatment alternatives.
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206A-MCC
General Session III
Contributed Session
Chair: Seyedali Mirzapour, PhD Student, Wichita State University,
1845 Fairmount St., Wichita, KS, 67260, United States,
1 - Modeling And Performance Evaluation Of Bernoulli Transfer Lines
With Batch Processors
Feiyi Yan, Northwestern Polytechnical University, 127 West Youyi
Road, Xi’an, China, , Jun-Qiang Wang
This paper focuses on analytical methods for performance evaluation of transfer
lines with Bernoulli unreliable batch processors and finite buffers. Each machine
has a limited capacity to process a batch of parts simultaneously. Three different
analytical models of production lines with two batch processors are established.
The modulo n congruence class theory is introduced to depict the system state of
the Markov chain and to prove the ergodicity condition. An aggregation method
is proposed to analyze a general Bernoulli transfer lines. Numerical experiments
are conducted to verify the accuracy of the proposed methods. The impact of
machine capacity on system performance is analyzed.
2 - A New Relaxation Method For Mathematical Program With
Complementarity Constraint
Tangi Migot, IRMAR-INSA, Rennes, France,
, Jean-Pierre Dussault, Mounir Haddou
p { margin-bottom: 0.25cm; line-height: 120%; } Recent progress on optimality
conditions for MPCC allows to build efficient relaxation methods starting from
Kadrani et al. in 2009. We will present an overview on these methods and discuss
both the properties of the sequence of non-linear program (NLP) generated by
these algorithms and the weakest conditions needed to ensure convergence of the
methods. We will also present a new method with improved properties on the
sequence of NLP, which provides a certificate when the method converges to
undesirable points. We run a numerical comparison of these methods on a large
number of test problems.
3 - Leaf Trajectory Optimization For Dynamic Delivery Of
Intensity-modulated Radiotherapy Plans
Seyedali Mirzapour, PhD Student, Wichita State University,
1845 Fairmount St., Wichita, KS, 67260, United States,
, Ehsan Salari
In intensity-modulated radiotherapy, a multi-leaf collimator (MLC) consisting of
rows of paired leaves, is used to dynamically modulate the shape and intensity of
radiation beams. Traditionally, unidirectional leaf sweeping schemes have been
considered for dynamic beam modulation. In this research, we investigate the
potential gain in plan quality and efficiency obtained from allowing for a free
movement of MLC leaves.
WE39
207A-MCC
Applied Probability and Economics II
Sponsored: Applied Probability
Sponsored Session
Chair: Krishnamurthy Iyer, Cornell University, 225 Rhodes Hall, Ithaca,
NY, 14853, United States,
1 - The Magician’s Shuffle: Re-using Lottery Numbers For School
Seat Redistribution
Irene Yuan Lo, Columbia University, New York, NY, United States,
, Itai Feigenbaum, Yashodhan Kanoria,
Jay Sethuraman
We consider a dynamic model of the school choice problem, where students are
given an initial allocation, learn the value of their outside option, and are then
given a final allocation based on their updated preferences. The goal is to obtain
an efficient final allocation that is individually rational with respect to the initial
allocation and minimizes student movement. We propose a family of mechanisms
that are fair, efficient, two-round strategy-proof and individually rational. We
show that when a natural ‘order’ condition is satisfied, all these mechanisms
produce equivalent final allocations, and that the mechanism that reverses
student lotteries between rounds minimizes student movement.
2 - Promotional Campaigns Under Social Learning
Ehsan Valavi, Columbia University, New York, NY, 30332-0205,
United States, Costis Maglaras
We study some promotional pricing heuristics in settings where consumers get
informed about a product through a product reviews via a social learning
mechanism.
3 - The Strange Case Of Privacy In Equilibrium Models
Rachel Cummings, California Institute of Technology, 1200 E
California Blvd, MC 305-16, Pasadena, CA, 91125, United States,
We study how privacy technologies affect user and advertiser behavior in a simple
economic model of targeted advertising. In our model, a consumer first decides
whether or not to buy a good, and then an advertiser chooses an ad to show her.
The advertiser would like to use information about the consumer’s purchase
decision to target the ad that he shows, but he is given only a differentially private
signal about the consumer’s behavior. We study equilibrium behavior as a
function of the privacy level and show that this behavior can be highly counter-
intuitive. The effect of adding privacy in equilibrium can be completely different
from what we would expect if we ignored equilibrium incentives.
4 - Delay-predictability Tradeoffs In Reaching A Secret Goal
Kuang Xu, Stanford University, Stanford, CA, United States,
, John N. Tsitsiklis
We formulate a model of dynamic decision-making to study an agent’s
predictability as she attempts to reach a final goal through a sequence of
intermediate actions, while watched by an adversary who tries to predict the goal
before it is reached. We are motivated by the increasing ubiquity of large-scale
data collection infrastructures capable of predicting an agent’s intentions and
future actions, in juxtaposition with an agent’s desire for privacy. We show the
predictability of the agent’s goal can be made inversely proportional to the time
she spends reaching it, and that this is the best possible. This characterization does
not depend on the structure of the agent’s state space beyond the diameter.
WE40
207B-MCC
Queues with Correlations
Sponsored: Applied Probability
Sponsored Session
Chair: Ohad Perry, Northwestern University - Evanston, Evanston, IL,
United States,
1 - The Impact Of Delays On Service Times In The Intensive Care Unit
Carri Chan, Columbia Business School,
Most queueing models used to model healthcare delivery ignore the effects of
delay experienced by patients awaiting care. We empirically verify that delays in
time-to-treatment can increase a patient’s service requirement. We then propose
a queueing model which incorporates these measured delay effects and
approximation the expected work in the system when the service time of a job is
adversely impacted by the delay experienced by that job. Our approximation
demonstrates that work grows much faster than the traditional 1/(1 − )
relationship seen in most queueing systems. As such, ignoring this effect of delay
could have dire operational consequences.
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