2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
60
2 - Shipment Consolidation And Dispatching Problem At
Ekol Logistics
Sinem Tokcaer, zmir University of Economics, Izmir, Turkey,
Ozgur Ozpeynirci, Muhittin H. Demir,
Irem Celik
The case considers international freight forwarding operations in Ekol Logistics of
Turkey; a leading international logistics company. Less-than-truckload orders are
routed either directly to destination, or through a cross dock. Currently, the
consolidation and dispatching plan is done manually. The case has two phases:
first, students analyze the cost structure to determine the total cost for a given
plan and suggest a better one. The second phase involves the construction of the
mathematical programming formulation to identify an optimal plan. Students are
also required to identify alternative feasible routes to be fed into the formulation,
in search for an improved optimal plan.
3 - Inventory Optimization For Rent The Runway
Vincent Slaugh, Cornell University, Ithaca, NY, United States,
Sridhar Tayur
The choice of how many rental dresses to procure in advance of each fashion
season plays a critical role in the success of Rent the Runway, an online high-
fashion dress rental business. The case leads students through this inventory
optimization decision for a single dress style using both queueing and Monte
Carlo simulation models implemented in a spreadsheet. Students are encouraged
to consider the strengths and weaknesses of each modeling approach and how to
incorporate additional model features such as nonstationary demand and the
random loss of rental units.
4 - The Safe Birth Clinic
Milind Dawande, The University of Texas at Dallas,
Richardson, TX, United States, , Tim Huh,
Ganesh Janakiraman, Mahesh Nagarajan, Yang Bo
The effective utilization of capacity is an important operational goal that managers
strive to achieve. Most textbooks use the following simple “bottleneck formula” to
calculate process capacity: the capacity of each resource is first calculated by
examining that resource in isolation; process capacity is then taken as the smallest
(bottleneck) among the capacities of the resources. The main goal of this case is to
alert students that, for processes in which activities share resources, the use of the
bottleneck formula brings the potential danger of reaching incorrect conclusions
about process capacity and may eventually lead to erroneous decisions with
significant financial impact.
SB50
212-MCC
Decision Making in Healthcare
Sponsored: Minority Issues
Sponsored Session
Chair: Shannon Harris, Ohio State University, 600 Fisher Hall,
Columbus, OH, 43210, United States,
1 - Simulation Optimization To Inform Decision Making In Birth
Karen T Hicklin, University of North Carolina, Chapel Hill, NC,
United States, , Julie Ivy
Of the nearly 4 million births that occur each year in the U.S., almost 1 in 3 is a
cesarean section (C-section). Due to the various increased risks associated with C-
sections and the potential major complications in subsequent pregnancies, a
re-evaluation of the C-section rate has been a topic of major concern. We present
a discrete event simulation model of women undergoing a trial of labor with the
goals to: (1) model the natural progression of labor for spontaneous and induced
laboring patients and (2) optimally decide when an intervention is needed, such
as augmentation or C-section, in order to reduce the number of C-sections due to
a “failure-to-progress” diagnosis.
2 - Dynamic Control Of A Single Server System When Jobs
Change Status
Gabriel Zayas-Caban, University of Michigan,
Many systems must contend with allocating resources to jobs whose initial service
requirements or costs change when they wait too long. We present a new
queueing model for this scenario and use a Markov decision process formulation
to analyze assignment policies that minimize holding costs. We provide sufficient
conditions under which simple priority rules hold and for when switching curve
structures hold. In general, we find that allowing service and/or cost
requirements to change changes the structure of optimal controls for resource
allocation in queueing systems.
3 - Online Overbooking Strategies In Outpatient Specialty Clinics
With No-shows And Advance Cancellations
Shannon Harris, Ohio State University,
Jerrold H May, Luis G Vargas
Patient behavior, such as no-shows and cancellations, can lead to issues that
heighten outpatient clinic access issues. In this paper, we develop strategies to
determine if and when to overbook patients, over a finite horizon, in an online
scheduling environment. We incorporate clinic parameters, no-shows, and
cancellations to inform the overbooking decisions. We find that the optimal
overbooking strategies are a function of both no-shows and cancellations, and
that a clinic can, under certain conditions, achieve a greater service reward by
overbooking patients than it can by not overbooking. Our work is motivated, in
part, by our observations of scheduling at a VHA specialty clinic.
4 - Modeling For The Equitable And Effective Distribution Of Food
Donations Under Stochastic Capacities
Irem Sengul Orgut, Quality Analytics Project Manager,
Lenovo, Raleigh, NC, United States, Julie Ivy,
Reha Uzsoy
Food insecurity is an increasing threat to people’s health status and quality of life.
In partnership with the Food Bank of Central and Eastern North Carolina, which
distributes donated food to a 34-county service area, our objective is to achieve
equitable and effective food distribution among the population at risk for hunger.
Counties’ capacities are the main source of uncertainty in this system as they
constrain the total food distribution due to the need to distribute food equitably.
We develop stochastic models for optimal food distribution and prove structural
results. We illustrate our results and perform an extensive numerical study using
historical data from our collaborating food bank.
SB51
213-MCC
Emergency Response, Recovery, and Resilience
Sponsored: Public Sector OR
Sponsored Session
Chair: Laura Albert McLay, University of Wisconsin-Madison, 3218
Mechanical Engineering Building, 1513 University Avenue, Madison,
WI, 53706, United States,
1 - Resilience-based Component Importance Measures For
Interdependent Infrastructure Networks
Yasser Almoghathawi, University of Oklahoma, Norman, OK,
United States,
Kash Barker
Interdependent infrastructure networks are subjected to disruptions due to
different disruptive events. Consequently, a failure in one network could lead to a
failure in another network. We propose two resilience-based component
importance measures to quantify the impact of the disrupted components on the
resilience of the interdependent infrastructure networks and rank them according
to their criticality to focus on preparedness efforts.
2 - An Integrated Network Design And Scheduling Problem For
Network Recovery And Emergency Response
Suzan Afacan, Graduate Student, University of Wisconsin-
Madison, Madison, WI, 53705, United States, ,
Laura Albert McLay
Infrastructure recovery is important for delivering time-sensitive services and
commodities after a disaster while also repairing network damage. To examine
this issue, we present an extension of the p-median problem in the case of
extreme events. In the model, we coordinate two types of service providers: (1)
recovery crews who repair disrupted roads and (2) emergency responders who
deliver services and commodities. The objective is to minimize the cumulative
weighted distance between the emergency responders and the calls for service
over the time horizon. We also present a new backup coverage model with the
same extension. The models are illustrated with the computational examples.
3 - Dynamic Programming For Ambulance Fleet Management
Amir Rastpour, Postdoctoral Fellow, University of Western
Ontario, Ivey Business School, 1255 Western Road,, London, ON,
N6G0N1, Canada, Mehmet A. Begen,
Armann Ingolfsson, Greg Zaric
We use dynamic programming to model ambulance systems. Our model can
potentially assist ambulance dispatchers to proactively take actions to avoid high
operational costs, lost calls, and the proportions of urgent calls that are not
covered timely, or a weighted sum of these performance measures. Possible
actions that we consider are: Calling in additional ambulances from neighboring
cities, expediting the service, and repositioning available ambulances following a
desired compliance table. We use a detailed simulation model to validate our
results.
SB50