Informs 2015

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INFORMS Philadelphia – 2015
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42-Room 102B, CC
Joint Session MSOM-Health/HAS: Healthcare
Analytics and Optimization
Sponsor: Manufacturing & Service Oper Mgmt/
Healthcare & HAS Operations
Sponsored Session
Chair: Anahita Khojandi, Assistant Professor, University of Tennessee,
Knoxville, TN, United States of America,
1 - Estimating Lipid Management Guidelines’ Risk Value of a Life
Year on Treatment
Murat Kurt, Merck Research Labs, 351 N. Sumneytown Pike,
North Wales, PA, 19454, United States of America,
Niraj Pandey, Mark Karwan
Statins reduce the risk of heart attack and stroke with adverse side effects, but
how to quantify these effects to help physicians make treatment decisions
remains to be an open question. We gauge these adverse effects for patients with
Type 2 diabetes from a central policy maker’s point of view by formulating a
dynamic decision model in which the objective is to minimize the risk of a first
major cardiovascular event where time spent on treatment is penalized by a
perceived risk increase. We seek penalty factors that make published lipid
management guidelines as close as possible to optimal. We present computational
results using clinical data and derive insights.
2 - Predicting No-show Behavior of Patients at a Mental Health Clinic
Fan Wang, University of Arkansas, 4207 Bell Engineering Center,
Fayetteville, AR, United States of America,
, Shengfan Zhang
Mental health clinics have relatively high no-show rates of patients, which reduce
provider productivity and clinic efficiency. This study presents two approaches for
no-show prediction: a logistic regression model and an artificial neural network.
The models are formulated using multiple factors including visit type, ICD-9
classification, insurance type, lead time to visit, no-show history, month, weekday
and hour. The predictive performances are evaluated based on AUC values.
3 - Optimizing Dynamic Interventions in Sleep Studies
Maryam Zokaeinikoo, Graduate Research Assistant, University of
Tennessee, 1700W. Clinch Ave., Apt. 505, Knoxville, TN, 37916,
United States of America, Anahita
Khojandi, Oleg Shylo
We discuss a mathematical framework that takes advantage of the technological
advances in wearable neuro-headsets to provide an objective, reliable,
inexpensive and scalable approach to sleep interventions. This framework is based
on semi-Markov decision models that rely on general signal processing methods
for continuous sleep assessment.
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43-Room 103A, CC
Joint Session RMP/PPSN: Socially Responsible
Revenue Models
Sponsor: Revenue Management and Pricing & PPSN
Sponsored Session
Chair: Ioana Popescu, INSEAD, 1 Ayer Rajah Avenue, 138676,
Singapore, Singapore,
1 - Is It Enough? Evidence from a Natural Experiment in India’s
Agricultural Markets
Kamalini Ramdas, , Nicos Savva,
Chris Parker
Does access to timely and accurate information provided through ICT applications
have additional impact over and above access to mobile phones, in improving
market efficiency? Using data from the Reuters Market Light text message service
in India that provides daily price information to market participants and a natural
experiment where bulk text messages were banned unexpectedly, we find that
this information reduces crop price dispersion by about 12%, over and above
access to mobile phones.
2 - Certainty Equivalent Planning for Multi-product
Batch Differentiation
Yang Wang, UC Berkeley, IEOR Dept., Berkeley, CA, 48109,
United States of America, ,
Philip Kaminsky, Stefanus Jasin
Motivated by a problem in biopharmaceutical manufacturing, we consider a
discrete time finite horizon inventory problem where several retailers place orders
to meet stochastic demand, and in each period, the sum of order quantities across
retailers must be a multiple of a standard batch size. We propose several easy-to-
implement heuristics using certainty equivalence and derive their performance
bounds analytically.
3 - Bridging the Gap between for Profit and Social
Responsibility Strategies
Enno Siemsen, Associate Professor, University of Minnesota, 321
19th Ave S, Minneapolis, MN, 55455, United States of America,
, Lisa Jones-christensen,
Sridhar Balasubramanian
This field experiment compares two different for-profit market entry strategies
with a philanthropic strategy in terms of how each influences consumer behavior
in base-of-the-pyramid communities. We analyze reactions to a water purification
product offered at three price points (moderate discount, deep discount, and free)
in rural Malawi.
4 - Revenue Models for Providing Clean Energy at the Bottom
of the Pyramid
Ioana Popescu, INSEAD, 1 Ayer Rajah Avenue, 138676,
Singapore, Singapore,
Bhavani Shanker Uppari, Serguei Netessine
One in every five people does not have access to electricity, relying mostly on
kerosene for light. Solar technologies are healthier and offer greater value, yet
they require significant one-time investments which are not affordable to people
living on $2/day. We develop a consumer behavior model that accounts for
income variability and liquidity constraints specific to bottom of the pyramid
markets, and investigate alternative revenue models, based on a case study in
Rwanda.
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44-Room 103B, CC
Revenue Optimization and Related Methodologies
Sponsor: Revenue Management and Pricing
Sponsored Session
Chair: Michael Katehakis, Professor And Chair, Rutgers University,
100 Rockafeller Road, Room, Piscataway, NJ, 08854,
United States of America,
1 - An Inventory System with Multiple Demand Classes
Min Wang, Assistant Professor, Drexel University, 3220 Market
St, Gerri C. LeBow Hall 740, Philadelphia, PA, 19104,
United States of America,
We consider a single-product inventory system with multiple demand classes.
Inventories are replenished using a (R, Q) policy and are rationed among demand
classes according to a threshold policy. We establish structural results for the key
performance measures and develop an efficient algorithm for computing the
policy parameters.
2 - Optimal Pricing for a GI/M/k/N Queue with Several Customer
Types and Holding Costs
Eugene Feinberg, Distinguished Professor, Stony Brook
University, Department of Applied Mathematics & Stat,
Stony Brook, NY, United States of America,
, Fenghsu Yang
This paper deals with optimal pricing for a GI/M/k/N queueing system with
several types of customers. A price for a new arrival depends on the number of
customers in the system. In addition, the system incurs costs caused customer
delays. The holding costs are non-decreasing and convex with respect to the
number of customers in the queue. This paper describes average-reward optimal,
canonical, bias optimal, and Blackwell optimal policies for this pricing problem.
3 - Efficient Markov Models for Dynamic Pricing Problems
Laurens Smit, Leiden University, Niels Bohrweg 2, Leiden,
Netherlands, , Flora Spieksma, Michael Katehakis
We model revenue problems as a two dimensional Markov chain, where the
arrival rate of customers depend on the charged price. We consider processes that
satisfy down entrance state or the restart entrance state classes of quasi skip free
processes. We derive explicit solutions and bounds for the steady state
probabilities of both processes, and show that these methods work fast and
efficiently. In addition we present a procedure to decompose Markov processes
into separate thinned processes.
4 - Models and Problems of Dynamic Pricing in the Multi-armed
Bandit Framework
Wesley Cowan, Rutgers University, 110 Frelinghuysen Rd.,
Piscataway, NJ, United States of America,
Michael Katehakis
After a brief review of basic issues of dynamic pricing under partial information
on the underlying demand distributions, we provide new models that address
some of these issues. A main contribution is a new model and solutions for
problems that involve unobserved lost sales.
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