2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
101
SD22
107B-MCC
Disaster Relief Supply Chains and Operations
Sponsored: Public Sector OR
Sponsored Session
Chair: Felipe Aros-Vera, Ohio University, Stocker Center 277, 1 Ohio
University, Athens OH, OH, 45701, United States,
1 - Pre-positioning Emergency Relief Items Before A Typhoon With
An Uncertain Trajectory
Joline Uichanco, University of Michigan, Ross School of Business,
We describe a collaborative work with the Philippine government on a pre-
positioning model in preparation for an oncoming typhoon. Pre-positioning relief
aid before a typhoon is challenging due to the uncertainties in locations and
quantities of future demand. We develop a prediction model for the number of
affected population by fitting a dataset of typhoon effects to a hierarchical linear
model. Our model reveals a significant relationship between wind speed and
affected population. We propose a bi-objective stochastic pre-positioning model
which balances fairness and effectiveness of the pre-positioning strategy.
2 - Ecuador Earthquake Relief Support: Observations From
Fieldwork Research
Johanna Amaya, Rensselaer Polytechnic Institute, Troy, NY,
United States, Johanna Amaya, Iowa State
University, Ames, IA, 50011, United States, ,
Cinthia Perez Siguenza, Jose Holguin-Veras
This talk presents an overview of the disaster response logistics that took place
after the earthquake in Ecuador. The talk discusses the preliminary results of the
fieldwork research conducted by the authors in the aftermath of the disaster.
3 - Objectives’ Misalignment In Humanitarian Operations:
The Role Of Earmarking
Laura Turrini, Kuehne Logistics University,
Maria Besiou
Effectiveness of humanitarian programs depends both on the donors’ willingness
to support the program and on the program implementation by the international
humanitarian organization (IHO). Donors donate with the aim of reaching as
more beneficiaries as possible. IHOs also have the same objective, but face
constraints on how they can use the available funds. A big constraint comes from
the donors themselves, who often earmark their funding. In this paper, we
analyze the donors’ and IHOs’ decision-making in an effort to shed more light on
how decisions for earmarking are taken. The aim is to give recommendations to
the IHOs on how to align donors’ objectives to theirs.
4 - Willingness-to-pay Models On Post-disaster Environments
Diana Ramirez-Rios, Research Assistant, Rensselaer Polytechnic
Institute, Troy, NY, 12180, United States,
Jose Holguin-Veras, Johanna Amaya, Trilce Marie Encarnacion,
Shaligram Pokharel, Victor Cantillo, Luk Wassenhove
This paper introduces an economic valuation for the level of anxiety of an
individual under deprivation conditions as anxiety is well-known measure of
psychological distress in a community. More specifically, this research estimated
the willingness-to-pay for water of individuals who have been affected by
disasters, under different scenarios of deprivation and expectation. The level of
anxiety is measured by the effect that the expected time to normality introduces
to WTP, and results indicate that that as the time to recover increases, the level of
suffering increases. “
SD23
108-MCC
Applications in Physician Scheduling
Sponsored: Health Applications
Sponsored Session
Chair: Andreas Fügener, Universität zu Köln, 123334, Germany,
1 - Decision Support For Physician Rostering: Development Of
Models And Implementation Of Software
Jens Brunner, University of Augsburg,
, Andreas Fuegener
In order to cope with steadily increasing healthcare costs, hospitals try to schedule
their physicians efficiently and effectively. We consider a scheduling problem at
large teaching hospitals in Germany. We formulate mixed-integer linear
programming models for duty- and workstation assignments subject to union
contracts as well as individual agreements of the physicians. To promote for job
satisfaction we take into account fairness and preferences. We present the status
of the software development and discuss lessons learned from the project and
highlight some barriers when it comes to implementation of decision support
systems in practice.
2 - Neonatal Physician Scheduling At The University Of Tennessee
Medical Center
Charles E Noon, University of Tennessee-Knoxville, Knoxville, TN,
United States, Melissa R Bowers, Wei Wu,
Kirk Bass
The default approach for scheduling hospital coverage is to distribute the various
types of shifts equally among the covering physicians. This “equality” approach
insures that each physician works his/her fair share of overnights, weekends, etc.
We present a new model that incorporates individual shift-type preference so that
each physician attains a schedule that is equivalent or superior to his/her
“equality” schedule. We formulate and solve the model as a mixed integer
program. We demonstrate its benefits by using the approach to schedule hospital
coverage for a neonatology group.
3 - Equitable Scheduling Of Resident Shifts
Hernan Abeledo, George Washington University,
Anthony Coudert
Creating shift schedules for resident physicians is a notoriously difficult task that
is typically done manually by the chief residents. Shift assignments need to
observe a large number of rules while populating a complex schedule structure. A
key goal is that the schedule be perceived as fair by all residents. We present an
integer programming model used to schedule anesthesiology residents at the
George Washington University Hospital. The fairness objective is addressed
through a point system proposed by the residents.
4 - Re-scheduling Of Physicians In Case Of Unexpected Absences
Andreas Fügener, University of Cologne,
Christopher Gross, Jens Brunner
Scheduling physicians is a complex task as legal requirements, levels of
qualification, and preferences for different working hours should be considered.
Unplanned absences, e.g. due to illness, additionally drive the complexity. In this
study, we discuss an approach to deal with the following trade-off: Changes to the
existing plan should be kept as small as possible. However, an updated plan
should still meet the requirements regarding work regulation, qualifications
needed, and employee preferences. We present a mixed-integer programming
model to create updated plans following absences of scheduled personnel and
apply it to real-life data from a German university hospital.
SD24
109-MCC
New Directions in Non-Market Strategies
Invited: Strategy Science
Invited Session
Chair: Jason Snyder, University of Utah, Eccles School, Salt Lake City,
UT, 9, United States,
1 - Locked In? Noncompete Enforceability And The Mobility And
Earnings Of High-tech Workers
Jin Woo Chang`, University of Michigan, Ann Arbor, MI, United
States, Natarajan Balasubramanian,
Mariko Sakakibara, Jagadeesh Sivadasan, Evan Starr
We use matched employer-employee data from 30 U.S. states to examine how the
enforceability of noncompete contracts affects the length of job spells and the
level of wages. Exploiting inter-state variation in the degree of enforceability and
controlling for worker-, job-, and state-level characteristics, we find that a unit
standard deviation increase in enforceability is associated with a 3.6% increase in
the length of job-spells for high-wage workers in technology industries. We also
find persistent wage suppressing effects that last throughout their employment
history. Together, these are consistent with noncompetes reducing the bargaining
power of employees relative to their employers.
2 - On A Firm’s Optimal Response To Pressure For Gender
Pay Equity
David Ross, University of Florida, 55, Gainesville, FL, 32611,
United States,
David Anderson, Cristian Dezsö, Margret Bjarnadottir
We present a theory of how a firm would respond to pressure for gender pay
equity by strategically distributing raises and adjusting its organizational structure.
Using mathematical reasoning, simulations, and data from a real employer, we
show that (a) employees in low-paying jobs and whose job-related traits typify
men at the firm are most likely to get raises; (b) counterintuitively, some men will
get raises and giving raises to certain women would increase the pay gap; (c) a
firm can reduce the gender pay gap as measured by a much larger percentage
than the overall increase in pay to women at the firm; and (d) “ghettoizing”
women in select jobs can help a firm reduce its pay gap.
SD24