2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - Decoupling Job Size And Server Slowdown In
Modeling Redundancy
Kristen Gardner, Carnegie Mellon University, 5000 Forbes Ave,
Pittsburgh, PA, 15213, United States,
Mor Harchol-Balter, Alan Scheller-Wolf
Redundancy is an increasingly common technique for reducing response time in
multi-server queueing systems. In a system with redundancy, jobs replicate
themselves and wait in multiple queues; a job is complete as soon as any one
copy completes service. Much of the existing theoretical work on analyzing
systems with redundancy makes the unrealistic assumption that a job’s service
times are independent across different servers. This assumption can lead to results
that are at odds with implementation results. We introduce a new, more realistic
model of redundancy and design a new dispatching policy that is both analytically
tractable within our model and has provably excellent performance.
3 - Gated Queues With Impatience Customers
George Mytalas, NJIT, Newark,NJ, NJ, United States,
We analyze an M/M/1 queueing model with gated service discipline. In this
discipline there is a waiting room and a service queue. Each time the service
queue becomes empty all customers in the waiting room are instantaneously put
in the service queue. Customers in waiting room can be impatient after waiting a
random amount (or a certain) of time and abandon the system. We derive the
joint distribution of the number of customers in waiting room and service queue,
and obtain various quality of service measures.
4 - Appointment Systems Under Service Level Constraints
Rui Chen, University of Toronto, 105 St George St, Toronto, ON,
M5S 3E6, Canada, Rowan Wang,
Zhenzhen Yan, Saif Benjaafar, Oualid Jouini
We consider a new model of appointment scheduling where customers are given
the earliest possible appointment times under the service level constraint that the
expected waiting time of each individual customer cannot exceed a given
threshold. We apply the theory of majorization to analytically characterize the
structure of the optimal appointment schedule. We show that, the optimal inter-
appointment times increase with the order of arrivals. We prove that, when
customer service times follow an exponential distribution, our system converges
asymptotically to the D/M/1 queueing system as the number of arrivals
approaches infinity. We also extend our analysis to systems with multiple servers.
5 - Approximations For Heavily-loaded G/ Gi/n+ Gi Queues
Yao Yu, North Carolina State University, 4335-3 Avent Ferry Road,
Raleigh, NC, 27606, United States, , Yunan Liu,
Ward Whitt
Motivated by applications to service systems, we develop convenient engineering
approximation formulas for the steady-state performance of heavily-loaded
G/GI/n+GI multi-server queues. Based on established Gaussian many-server
heavy-traffic limits in the efficiency-driven regime, however, the approximations
also apply to systems in the quality-and-efficiency-driven regime where traffic
intensity is close to 1 from above. Simulation experiments show that the proposed
approximations are effective for large-scale queueing systems for a significant
range of the traffic intensity and the abandonment rate.
TB34
204-MCC
Scheduling and Workload Assignment in Healthcare
Sponsored: Manufacturing & Service Oper Mgmt, Healthcare
Operations
Sponsored Session
Chair: Retsef Levi, MIT, 100 Main Street, Building E62-562, Cambridge,
MA, 02142, United States,
Co-Chair: Cecilia Zenteno, Massachusetts General Hospital,
55 Fruit Street, White 400, Boston, MA, 02114, United States,
1 - Integrated Scheduling And Capacity Planning With
Considerations For Patients’ Length-of-stay
Nan Liu, Columbia University, New York, NY, United States,
, Van-Anh Truong, Xinshang Wang,
Brett Anderson
Motivated by the shortcoming of current hospital scheduling and capacity
planning methods which often model different units in isolation, we introduce
the first dynamic multi-day scheduling model that integrates information about
capacity usage at more than one location in a hospital. In particular, we analyze
the first dynamic model that accounts for patients’ length-of-stay and
downstream census in scheduling decisions. Through numerical experiments on
real data, we show that there is substantial value in making integrated scheduling
decisions. In contrast, localized decision rules that only focus on a single location
of a hospital can result in up to a three-fold increase in total expenses.
2 - An Approximate Dynamic Programming Approach To Online
Capacity Planning For Rehabilitation Treatment
Ingeborg A. Bikker, University of Twente, Enschede, Netherlands,
Ingeborg A. Bikker, Sint Maartenskliniek, Nijmegen, Netherlands,
, Martijn Mes, Richard J Boucherie
We study an online capacity planning problem in which rehabilitation patients
require a series of appointments with several disciplines, within a certain access
time. In practice, appointments are typically planned in the first available time
slots, leaving no space for urgent patients. In our research, we plan capacity for
the appointment series of a patient at the moment of his/her arrival, in such a
way that the total number of requests planned within their required access time is
maximized. We formulate this problem as a Markov decision process, that takes
into account predicted future arrivals. An approximate dynamic programming
approach is used to obtain approximate solutions.
3 - Real-time Assignment Of Inpatients To Care Teams And Beds
Aleida Braaksma, Massachusetts Institute of Technology,
100 Main Street, E62-389, Cambridge, MA, 02142, United States,
, Elizabeth Ugarph, Rhodes Berube,
Cecilia Zenteno, Walter O’Donnell, Retsef Levi
The Department of Medicine at Massachusetts General Hospital has undergone a
major care team and inpatient units redesign. In this work, we exploit the
potential of the redesign to develop algorithms for real-time assignment of
patients to care teams and to beds, aiming at shortening patient wait times, and
decreasing the load of Medicine patients boarding in the Emergency Department.
We use data-driven simulation to assess the effectiveness of the algorithms as well
as to evaluate several other interventions aimed at optimizing patient flow.
TB35
205A-MCC
Managing Service Systems with Strategic Servers
Sponsored: Manufacturing & Service Oper Mgmt,
Service Operations
Sponsored Session
Chair: Philipp Afeche, University of Toronto, Rotman School of
Management, Toronto, ON, M5S 3E6, Canada,
1 - Product Support Forums: Customers As Partners In The
Service Delivery
Stouras Konstantinos, INSEAD,
Serguei Netessine, Karan Girotra
Online product support forums where customers can post complaints and
questions, or report issues about a product or service of a firm abound. A large
number of companies choose to crowdsource their product and service support
back to their customers, employing a few dedicated service operators. We
characterize the equilibrium behavior of such a novel business model for service
and compare it with a call center model.
2 - Incentive Based Service System Design: Staffing And
Compensation To Trade Off Speed And Quality
Amy Ward, USC Marshall School of Business, Los Angeles, CA,
United States, Dongyuan Zhan
In many service systems, there is a trade-off between service speed and quality,
and employees are paid based on both. We assume that the employees each
selfishly choose their own service speed in order to maximize their own expected
utility, which can have both a monetary and a non-monetary component. We
show that a simple linear staffing and compensation policy is a first best solution
in a large system limit. We further show the conditions under which a critically
loaded, efficiency-driven, quality-driven, or mixed regime - in which there is
simultaneous customer abandonment and server idling - emerges under a first-
best linear policy.
3 - Managing Workplace Flexibility: The Case Of Agents With
Task Preferences
Vasiliki Kostami, London Business School, ,
Rouba Ibrahim
In many workplaces, employees are expected to excel in different skills as part of
their job and are usually heterogeneous in their preferences to perform certain
tasks. They might be willing to give up a grain of their salary to avoid working on
the unlikable ones or prioritize the preferred ones. The manager, in turn, gains
extra freedom in his decision to allocate tasks by charging his servers for this task
discretion. We study how the choices change in equilibrium and we also derive
the optimal flexibility fee under two innovative flexibility schemes and different
heterogeneity scenarios.
TB35