2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Delivering Long Term Surgical Care In Underserved Communities
Ujjal Kumar Mukherjee, University of Illinois at
Urbana–Champaign, Champiagn, IL, United States,
, Emily J. Kohnke, Kingshuk K Sinha
How can international NPOs enable the long-term delivery of surgical care in
underserved communities? We report findings from a longitudinal field study
spanning 11 years conducted at Gansu province of China. We triangulate insights
from qualitative and quantitative data analyses to develop and validate an
integrative framework that demonstrates how an international NPO’s efforts
related to affordability, provider-awareness, and access are interdependent, and
how the efforts interact and impact the volume and quality of surgeries in
underserved communities.
4 - Improving Societal Outcomes In The Organ Donation Value Chain
Priyank Arora, Georgia Institute of Technology,
800 W Peachtree St NW, Atlanta, GA, 30308, United States,
, Ravi Subramanian
Our paper studies the operational actions of supply-side players in an organ
donation value chain (ODVC), namely, the Organ Procurement Organization that
coordinates organ recovery activities, and the hospital, where potential cadaveric
donors arrive. The main contributions of our work are two-fold: First, while the
majority of the literature focuses on the demand side of an ODVC, we develop an
analytical model to study the effects of contextual parameters and decisions of the
supply-side entities in an ODVC on their respective payoffs and societal outcomes.
Second, we recommend Pareto-improving contracts that a social planner can use
to help the ODVC achieve socially-optimal performance.
WD24
109-MCC
Topics in Resident and Medical Student Scheduling
Sponsored: Health Applications
Sponsored Session
Chair: Amy Cohn, University of Michigan, 1205 Beal Avenue, Ann
Arbor, MI, 48109-2117, United States,
1 - Using Maximally Feasible And Minimally Infeasible Request Sets
To Construct Resident Schedules
Brian Lemay, University of Michigan, Ann Arbor, MI, United
States, , Amy Cohn, Marina Alex Epelman
When scheduling healthcare providers, it is frequently not possible to satisfy
every scheduling request. Multi-criteria objective functions provide one method
for overcoming this challenge, but can result in undesirable schedules. We discuss
an alternative method for resolving conflicting requests that identifies maximally
feasible and minimally infeasible sets of scheduling requests by solving a sequence
of optimization problems. We present results based on a resident scheduling
problem at a major teaching hospital.
2 - A General Model For Medical Resident Rotation Scheduling
William Pozehl, University of Michigan, ,
Amy Cohn
Building annual rotation schedules for medical residents is often extremely
challenging for program directors and chief residents. Scheduling requires a
complex tradeoff of resident needs, service needs, and a multitude of preferences
and requests. We present a general model for automatically constructing these
schedules using linear programming and explore algorithms for iteratively
improving the measures of schedule quality.
3 - Creating Resident Shift Schedules Under Multiple Objectives By
Generating And Evaluating The Pareto Frontier
Young-Chae Hong, University of Michigan, ,
Amy Cohn, Marina A Epelman
Preparing a schedule for residents is a complex task, which requires considering a
large number of complex rules and multiple conflicting metrics at the same time:
patient safety, educational requirements, and resident satisfaction. However, it is
not easy for chief residents to quantify weights to trade off metrics or to provide a
single objective function. Thus, it is better to provide a set of Pareto schedules to
the chief residents and make them choose the most preferable one. This research
uses integer programming and a recursive algorithm for generating Pareto
schedules to reduce the solution space for chief residents to review and to help
elicit their preferences.
4 - A Linear Programming Model For Scheduling Medical School
Clinical Experiences
Roshun Sankaran, University of Michigan, Ann Arbor, MI,
United States, Amy Cohn, Anna Munaco
The University of Michigan Medical School unveiled a new curriculum in 2015
aimed at providing medical students with a sustained balance of science
coursework and clinical exposure over their four years via the Initial Clinical
Experience (ICE) and M4 Pilot programs. Building schedules for these programs
are multi-criteria objective problems that consider constraints unique to each
course. Easy-to-use scheduling tools using Open Solver were developed to create
optimal group and clinic assignments for each program in order to streamline the
scheduling process in the future.
WD25
110A-MCC
Logistics IV
Contributed Session
Chair: Jafar Namdar, University of Tennessee, 2109 Laurel Avenue,
Knoxville, Knoxville, TN, 37916, United States,
1 - Designing Robust Beef Supply Chain With Environment And
Animal Welfare Costs: Small Or Large Slaughter Facilities
Faisal M. Alkaabneh, Huaizhu Oliver Gao, Cornell University,
Ithaca, NY, Contact:
We consider the problem of designing robust beef supply chain for some regions
in New York State by simulating supply and demand side shocks. We developed a
Mixed Integer Programming model that decides simultaneously the assignment
of beef slaughter facilities to beef feedlots, locating slaughter facilities, and rout-
ing of trucks from slaughter facilities to a set of customers. The problem under
consideration takes into account environmental costs and animal welfare. We
show how the structure of the supply chain changes when considering environ-
mental cost and animal welfare and how the promotion of small slaughter facili-
ties provides more agile and robust network under different scenarios.
2 - Smart Logistic Management
Mostafa Ghafoorivarzaneh, Student, University of Tennessee-
Knoxville, 851 Neyland Drive, Room 511, Knoxville, TN, 37996,
United States, , Roshanak Akram,
Rupy Sawhney
In this study, a smart logistic management approach will be introduced. First a set
of KPIs will be discussed for logistic management, which are mostly in tactical
level of supply chain. At the second step information needed for smart logistic
management will be collected and visualized automatically. In the third step a
time dependent Periodic VRP will be introduced based on collected information in
second step using a meta-heuristic approach. In the last section a heuristic
rerouting method will be introduced based on collected information in second
and third steps.
3 - A Robust Model Predictive Control Approach For Logistics
Planning In Response To An Earthquake
Yajie Liu, Associate Professor, National University of Defense
Technology, Changsha, 410073, China, ,
Hongtao Lei, Jianmai Shi
Making transportation plans usually faces many challenges in response to
earthquakes, especially when the post-disaster environment is dynamic and
uncertain. This study provides a model predictive control (MPC) approach
combined with robust optimization (RO) to the problem of efficiently transporting
both commodities to affected areas and injured people to hospitals in post-disaster
stage, in which the MPC approach is utilized to adjust to frequent updated
information and RO is used to deal with uncertainties on each decision making
point. At the end, a numerical example demonstrates the feasibility and
effectiveness of our proposed approach.
4 - Designing A Resilient Supply Chain Network
Jafar Namdar, University of Tennessee, 2109 Laurel Avenue,
Knoxville, Knoxville, TN, 37916, United States,
, Rapinder Sawhney, Nooshin Hamidian
This paper investigates different sourcing strategies to achieve supply chain
resilience under disruptions aiming for a deeper understanding of how supply
chain characteristics are related to resilience and how to better support disruption
planning and mitigation. Specifically, we consider different coping strategies,
including a single sourcing versus multiple sourcing, signing contract with backup
supplier, spot purchasing, collaboration and visibility.
WD25