2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
310
TC24
109-MCC
Public Health and Health System Modeling
Sponsored: Health Applications
Sponsored Session
Chair: Stan Neil Finkelstein, MIT, 77 Massachusetts Avenue,
Cambridge, MA, 02139, United States,
1 - A Dynamic Model Of Post-traumatic Stress Disorder For Military
Personnel And Veterans
Navid Ghaffarzadegan, Virginia Tech, 307 Craig Dr., Blacksburg,
VA, 24060, United States, , Alireza Ebrahimvandi,
Mohammad S. Jalali
The importance and complexity of PTSD raise a critical question: What are the
future trends in the population of PTSD patients among military personnel and
veterans? We developed a system dynamics simulation model of the population of
combat-related PTSD patients. The model is validated by replicating the historical
data from 2000 to 2014. It forecasts PTSD prevalence, and estimates costs for the
military and the VA under various policies and scenarios. One particular finding is
that in a postwar period, current health policy interventions have only marginal
effects on mitigating the problem of PTSD.
2 - Modeling Food Supply Systems To Identify Outbreak Origins
Elena Polozova, Undergraduate Student, Massachusetts Institute of
Technology, 77 Massachusetts Ave., Cambridge, MA, 02139,
United States, Abigail Lauren Horn,
Andreas Balster, Hanno Friedrich
The aim of this research is to efficiently identify the source of large-scale
outbreaks of foodborne disease while contamination-caused illnesses are still
occurring, thereby resolving investigations earlier and averting potential illnesses.
We propose a holistic system for real-time source detection, which combines a
dynamic model of commodity flows with a spatio-temporal method for source
localization on networks. We evaluate the ability of the system to identify the
source of simulated outbreaks and real historical outbreaks of foodborne disease
in Germany, quantifying benefits in comparison to current methods in outbreak
identification.
TC25
110A-MCC
Scheduling in Practice
Invited: Project Management and Scheduling
Invited Session
Chair: Emrah Cimren, Nike, Portland, OR, United States,
1 - Integrated Staffing And Scheduling In Call Centers Using Dynamic
Queueing Models
Raik Stolletz, University of Mannheim, Chair of Production
Management, Schloss, Mannheim, 68131, Germany,
Traditional sequential approaches derive staff requirements using queueing
models in a fist step and use these results as constraints in determinist shift
scheduling as a second step. We present a simultaneous approach, which
determines the shift schedule directly based on a forecast of the arrival rates, the
constraints on shift, and service level requirements.
We present a general stochastic optimization model for the simultaneous
approach. Based on an approximation method for time-dependent queues, we
will analyze the respective non-linear optimization model. In a numerical study
we compare both approaches.
2 - Scheduling Of Vehicles With Handover Relations At
Transshipment Terminals
Dirk Briskorn, University of Wuppertal,
Malte Fliedner, Martin Tschöke
We consider a generic problem arising when coordinating deliveries and
collections at a transshipment terminal. A set of vehicles and a set of doors given,
we distinguish between problem settings where each vehicle can be docked only
once, each vehicle can be docked multiple times at the same door, and each
vehicle can be docked multiple times at different doors. We have a set of
handover relations meaning that one vehicle delivers goods to be picked up by an
other. For such a handover relation to be satisfied the second vehicle must be
docked at some point of time after the first arrival of the first vehicle. We consider
settings where storing goods is allowed and settings where this is not the case and
investigate the computational complexity of finding a feasible docking policy.
3 - Staff Scheduling For Regular And On-call Hours In Retailers When
Sales Are Correlated With Store Traffic And Staffing
Osman Alp, University of Calgary, Haskayne School of Business,
2500 University Drive, Scurfield Hall 120, Calgary, AB, T2N1N4,
Canada,
Sales in retail stores are closely related to store traffic and level of staffing, among
other factors. We consider a retail store which can keep track of customer traffic
continuously and has the option of scheduling some of their staff on an on-call
basis in addition to their regular shift hours. Based on the observed store traffic,
retailer may summon the reserved on-call workers with an offset. We investigate
the staff scheduling problem of such retailers. The retailer aims to find an optimal
staff schedule for regular shifts, the number of on-call staff reserved for every
hour, and a decision rule to summon the workers if necessary. We propose a
model to solve this problem and conduct numerical analysis.
TC26
110B-MCC
Combinatorial Auctions
Invited: Auctions
Invited Session
Chair: Sven Seuken, University of Zurich, Zurich, Switzerland,
1 - Core-selecting Payment Rules For Combinatorial Auctions With
Uncertain Availability Of Goods
Dmitry Moor, University of Zurich, Zurich, Switzerland,
, Sven Seuken, Tobias Grubenmann,
Abraham Bernstein
In some auction domains, there is uncertainty regarding the final availability of
the goods being auctioned off. For example, a government auctioning off
spectrum from its public safety network may need this spectrum back in times of
emergency. In such a domain, standard combinatorial auctions perform poorly as
they lead to violations of individual rationality (IR), even in expectation, and to
very low efficiency. We present payment rules for such domains. We show that in
these domains, there does not exist a payment rule which is guaranteed to be ex-
post core-selecting. We then demonstrate that by making the rules
“execution-contingent”, we can reduce IR violations while achieving IR in
expectation.
2 - SATS: A Spectrum Auction Test Suite
Michael Weiss, tba, tba, Switzerland,
Benjamin Lubin, Sven Seuken
For the past 16 years, much of the work on combinatorial auctions (CAs) has
used the CATS instance generator [Leyton-Brown et al., 2000]. While this test
suite has been very beneficial to the community, it does not model spectrum
auctions particularly well, which in recent years have become the most important
application of CAs. In this talk, we introduce SATS, a new “spectrum auction test
suite,” providing a unified framework and code base for several of the spectrum
auction generators that have been proposed in the literature. Furthermore, we
include a novel generator that captures the important and difficult to model
geographic complementarities of auctions such as the 2014 Canadian auction.
3 - Design Of Combinatorial Auctions Using Machine
Learning-based Bidding
Gianluca Brero, University of Zurich, Zurich, Switzerland,
, Benjamin Lubin, Sven Seuken
Combinatorial auctions are attractive mechanisms to efficiently allocate resources
even when bidders have combinatorial valuations. However, the large number of
items sold in many real-world auctions prevents a direct application of
combinatorial auction formats. In particular, designing concise bidding languages
that do not constrain the bidders’ expressiveness is a challenging task. In this talk,
we will present a new paradigm for designing bidding languages based on
machine learning principles. We show that we can exploit simple knowledge
about bidders’ preferences to automatically design concise bidding languages that
don’t limit the expressiveness of the bidders.
4 - Designing A Combinatorial Market For Offloading Cellular Traffic
Via Wireless Access Points
Sven Seuken, University of Zurich,
We study a market where mobile network operators (MNOs) are enabled to
offload some of their peak-time cellular traffic via wireless access points. This is a
challenging domain because the MNOs have complex combinatorial preferences
regarding when and where to offload their cellular traffic. We first describe how
the MNOs’ preferences can be modeled succinctly. Then we introduce a
combinatorial allocation mechanism that computes an optimal allocation, i.e.,
which MNOs get to offload how much of their traffic in which of their cell sectors
and at what time of the day. Finally, we show how to use core-selecting
combinatorial auctions to computes prices for each MNO.
TC24