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November 7-8-9, 2016 Workshop on YEQT X
"Queueing Theory in Operations Research" part of STOCHASTIC ACTIVITY MONTH Data Driven Operations Management
SUMMARY The theme of this year’s YEQT workshop is "Queueing Theory in Operations Research", where we aim to discuss research that uses understanding gained from queueing theory to help make better decisions in a variety of fields of operations. In this workshop, we intend to build a queueing-theory oriented program around the following OR‐related applications: ˇ Communication networks ˇ Energy networks ˇ Traffic networks ˇ Service systems ˇ Healthcare systems
ORGANISERS *
* Scientific advisor: Onno Boxma (TU Eindhoven)
LIST OF SPEAKERSKEYNOTE/TUTORIAL SPEAKERS:
INVITED SPEAKERS
MONDAY NOVEMBER 7
TUESDAY NOVEMBER 8
WEDNESDAY NOVEMBER 9
ABSTRACTSRaisa Carmen How inpatient boarding affects emergency department performance: A queueing analysis Using a Markov-modulated fluid queue approach, this study seeks insights into the effect of boarding patients on emergency department performance, which is evaluated by expected waiting times, service levels, and maximum throughput. The elegant matrix-geometric property of the stationary distribution allows a more efficient calculation of service levels than the standard Quasi-birth-death method. The focal network features inpatient boarding; discontinuous treatment, such that patients may visit a physician more than once; and a semi-open structure, which ensures the capability to model limited bed capacity in addition to a limited physician capacity. Boarding reduction policies that focus on decreasing the boarding time perform better than policies that focus on decreasing the probability of boarding. Céline Comte Networks of multi-server queues with parallel processing We consider
a network of multi-class multi-server queues. Each job can be processed in
parallel by any subset of servers within a pre-defined set that depends on
its class. Each server is allocated in FCFS order at each queue. Jobs arrive
according to Poisson processes, have independent exponential service
requirements and are routed independently at random. We prove that, when
stable, the network has a product-form stationary distribution. From a
practical perspective, we propose an algorithm on this basis to allocate the
resources of a computer cluster according to balanced fairness. We finally
examine further developments of this model to allow for dynamic adaptation
to the system occupancy. Jim Dai Stein’s Method for Steady-State Approximations: Error Bounds and Engineering Solutions Through queueing systems modeling customer call centers
and hospital patient flows, I will give an introduction on how to use
Stein's method both as an engineering tool for generating good steady-state
approximations and as a mathematical too for establishing error bounds for
these approximations. These approximations are often universally accurate in
multiple parameter regions, from underloaded to overloaded (when abandonment
is possible). Matthias Deceuninck OR in
healthcare: data-driven appointment scheduling Ton Dieker
Approximations of Queueing Performance for Rapid Systems Design Jing Dong A Queueing Model for Internal Wards Hospital queues have unique features, which are not captured by standard queueing assumptions, necessitating the development of specialized models. In this work, we propose a queueing model that takes into account the most salient features of queues associated with large Internal Wards (IWs). We characterize the maximum long-run workload that the IW can handle, and introduce a deterministic (fluid) approximation for the non-stationary dynamics. The fluid model is shown to have a unique periodic equilibrium, so that long-run performance analysis can be carried out by simply considering that equilibrium. Consequently, evaluating the effects of policy changes on system's performance and optimizing long-run operational costs are facilitated considerably. Kristy Gardner A Better Model for Job Redundancy: Decoupling Server Slowdown and Job Size Recent computer systems research has proposed using redundant requests --
creating multiple copies of the same job and waiting for the first copy to
complete service -- to reduce latency. In the past few years, queueing
theorists have begun to study redundancy, first via approximations, and,
more recently, via exact analysis. Unfortunately, for analytical
tractability, most existing theoretical analysis has assumed a model in
which the replicas of a job each experience independent runtimes (service
times) at different servers. This model is unrealistic and has led to
theoretical results which can be at odds with computer systems
implementation results. We introduce a much more realistic model of
redundancy. Our model allows us to decouple the inherent job size (X) from
the server-side slowdown (S), where we track both S and X for each job.
Analysis within the S&X model is, of course, much more difficult.
Nevertheless, we design a policy, Redundant-to-Idle-Queue (RIQ) which is
both analytically tractable within the S&X model and has provably excellent
performance. Song-Hee Kim Refining Workload Measure in Hospital Units: From Census to Acuity-Adjusted Census in Intensive Care Units We aim to better understand the impact of Intensive Care Unit (ICU)
workload on patient outcomes, so that practitioners and researchers can use
such understanding to provide high quality care despite increased hospital
crowding. We use data collected from the medical ICU and the surgical ICU of
a major teaching hospital. We measure ICU workload in a novel way that takes
into account not only the census but also patient acuity. Having categorized
the ICU workload at time of patient departure as low census,
high-census/low-acuity, and high-census/high-acuity, we find that patients
discharged on a day of high-census/high-acuity ICU workload had
significantly worse health status than patients discharged from a low-census
ICU workload. Moreover, we find patients with poorer health status at the
time of ICU discharge experienced worse longer-term outcomes, including
longer post-ICU length-of-stay (LOS), higher mortality, and higher total
hospital costs. Athanasia Manou Strategic Behavior in Transportation Systems This research focuses on the behavior of strategic customers in transportation systems. We consider two different models. In the first model, arriving customers decide whether to join the transportation station or balk, based on a natural reward-cost structure that models their desire for service and their unwillingness to wait. Solving the game among customers, we determine their strategic behavior and explore the effect of key service parameters, such as the frequency and the punctuality of service, on customer behavior. In the second model, we assume that the administrator of the transportation system makes decisions as well. Specifically, arriving customers decide whether to join the station or balk and the administrator sets the fee. In this case, a two-stage game among the customers and the administrator takes place. We explore how system parameters affect the customer behavior and the fee imposed by the administrator. Moreover, we consider three cases distinguished by the level of delay information provided to customers at their arrival instants. We compare these three cases and show that the customers almost always prefer to know their exact waiting times whereas the administrator prefers to provide either no information or the exact waiting time depending on the system parameters. Gal Mendelson Heavy traffic analysis of redundancy routing and join the shortest queue policies We will present heavy traffic limit results on the JSQ and redundancy
routing policies for the parallel server model, with heterogeneous and fixed
number of servers. These include state space collapse, identification of the
limit and delay calculations. A key role is played by considering the
following link between the two policies: A policy that sends multiple
replica to a number of servers can otherwise be described as one which sends
only to the server having the least workload. Tommaso Nesti Reliability of DC Power Grids Under Uncertainty: \\a Large Deviations Approach The advent of renewable energy has huge implications for the design and control of power grids. Due to increasing supply-side uncertainty, traditional reliability constraints such as strict bounds on current, voltage and temperature in a transmission line have to be replaced by chance constraints which are computationally hard. In this talk we use large deviations techniques to study the probability of current and temperature overloads in a DC network with stochastic power injections, and develop corresponding safe capacity regions. In particular, we characterize the set of admissible power injections such that the probability of overloading of any line over a given time interval stays below a fixed target. We show how enforcing (stochastic) constraints on temperature, rather than on current, results in a less conservative approach and can thus lead to capacity gains in power grids. Brendan Patch Detecting Markov Chain Instability: A Monte Carlo Approach We devise a Monte Carlo based method for detecting
whether a non-negative Markov chain is stable for a given set of potential
parameterizations. More precisely, for a given set in parameter space, we
develop an algorithm that is capable of deciding whether the set has a
subset of positive Lebesgue measure for which the Markov chain is unstable.
The approach is based on a variant of simulated annealing, and consequently
only mild assumptions are needed to obtain performance guarantees. Arik Senderovich Optimal model simplification to improve performance
prediction in service processes Peter van de Ven Managing Appointment Scheduling under Patient Choices Motivated by the use of appointment templates in
healthcare scheduling practice, we study how to offer appointment slots to
patients in order to maximize the utilization of provider time. We develop
two models, non-sequential scheduling and sequential scheduling, to capture
different types of interactions between patients and the scheduling system.
In these models, the scheduler offers either a single set of appointment
slots, or multiple sets in sequence, for arriving patients to choose,
without knowing their preference information. For the non-sequential
scheduling model, we identify certain problem instances where the greedy
policy is suboptimal, but show through analytical and numerical results that
for most moderate and large instances, greedy performs remarkably well. For
the sequential model, we explicitly derive the optimal policy for a large
class of instances; for those that we cannot solve for the optimal policy in
closed-form, we develop an effective heuristic. Our case study, based on
real patient preference data, demonstrates a potentially up to 17%
improvement in provider capacity utilization by adopting our proposed
scheduling policy. Neil Walton Longest-Queue Shortest-Queue: the long and short of it! When arriving at a set of queues, it is natural to want to join the shortest and, when serving queues, it is natural to want to serve the longest. In this tutorial, we separately study Joint the Shortest Queue and Longest Queue First service. We discuss the consequences and generalizations of these decesion rules. We survey classical results and techniques, we discuss recent applications and motivating technologies. We apply contemporary methods to understand optima and passimal performance in these systems. Amy Ward Matching for Real-time Ridesharing In a ridesharing system such as Uber or Lyft, arriving customers must be
matched with available drivers. These decisions affect the overall number of
customers matched, because they impact whether or not future available
drivers will be close to the locations of arriving customers. A common
policy used in practice is the closest driver (CD) policy that offers an
arriving customer the closest driver. This is an attractive policy because
no parameter information is required. However, we expect that a
parameter-based policy can achieve better performance. Assaf Zeevi Observational Learning and Abandonment Behavior in Queues In several service operations settings users only have partial
information on system parameters pertinent to performance. In some cases it
may only be possible for them to infer this through their own observations
or experiences in the system. In this talk we present a simple stylized
model of a queueing system that strives to capture some salient features of
"observational learning," and elucidate its effects on user behavior and the
system's equilibrium operating point. Noa Zychlinski Bed Blocking in Hospitals due to Scarce Capacity in Geriatric Institutions -- Cost Minimization via Fluid Models This research focuses on elderly patients who have been hospitalized, are ready to be discharged but must remain in the hospital until a bed in a geriatric institution becomes available; these patients ``block" a hospital bed. Bed-blocking has become a challenge to healthcare operators due to its economic implications and quality-of-life effect on patients. Hospital-delayed patients, who cannot access their most appropriate treatment (e.g., rehabilitation), prevent new admissions. Moreover, bed-blocking is costly since a hospital bed is more expensive to operate than a geriatric bed. We are thus motivated to model and analyze the flow of patients between hospitals and geriatric institutions, in order to improve their joint operation. To this end, we develop a mathematical fluid model of this patient flow, which accounts for blocking, mortality and readmission, all significant features of the discussed environment. Analyzing the fluid model and its offered-load counterpart yields a closed-form expression for bed allocation decisions, which minimizes underage and overage costs. Finally, we validate the model with a two-year data set from a hospital chain, which includes four general hospitals and three geriatric hospitals. Solving for the optimal number of geriatric beds in our system demonstrates that significant cost reductions are achievable, when compared to current operations.
PRACTICAL INFORMATION● VenueEurandom, Mathematics and Computer Science Dept, TU Eindhoven, De Groene Loper 5, 5612 AZ EINDHOVEN, The Netherlands
Eurandom is located on the campus of
Eindhoven University of
Technology, in the
Metaforum building
(4th floor) (about
the building). The university is
located at 10 minutes walking distance from Eindhoven main railway station (take
the exit north side and walk towards the tall building on the right with the
sign TU/e).
● Registration
● Accommodation / FundingHotel will be booked for all invited speakers. Please give your arrival and departure date on the registration form. Other participants have to make their own arrangements. For hotels around the university, please see: Hotels (please note: prices listed are "best available"). More hotel options can be found on the webpages of the Tourist Information Eindhoven, Postbus 7, 5600 AA Eindhoven.
● TravelFor those arriving by plane, there is a convenient direct train connection between Amsterdam Schiphol airport and Eindhoven. This trip will take about one and a half hour. For more detailed information, please consult the NS travel information pages or see Eurandom web page location. Many low cost carriers also fly to Eindhoven Airport. There is a bus connection to the Eindhoven central railway station from the airport. (Bus route number 401) For details on departure times consult http://www.9292ov.nl The University can be reached easily by car from the highways leading to Eindhoven (for details, see our route descriptions or consult our map with highway connections.
● Conference facilities : Conference room, Metaforum Building MF11&12The meeting-room is equipped with a data projector, an overhead projector, a projection screen and a blackboard. Please note that speakers and participants making an oral presentation are kindly requested to bring their own laptop or their presentation on a memory stick.
● Conference SecretariatUpon arrival, participants should register with the workshop officer, and collect their name badges. The workshop officer will be present for the duration of the conference, taking care of the administrative aspects and the day-to-day running of the conference: registration, issuing certificates and receipts, etc.
● CancellationShould you need to cancel your participation, please contact Patty Koorn, the Workshop Officer.
● ContactMrs. Patty Koorn, Workshop Officer, Eurandom/TU Eindhoven, koorn@eurandom.tue.nl SPONSORSThe organizers acknowledge the financial support/sponsorship of:
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