2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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214-MCC
Proactive Planning Against Weather Events
Sponsored: Public Sector OR
Sponsored Session
Chair: Ozlem Ergun, Northeastern University, 453 Meserve,
360 Huntington Avenue, Boston, MD, 02115, United States,
Co-Chair: Mahsa Ghanbarpour Mamaghani, Northeastern University,
360 Huntington Avenue, Boston, MA, 02115, United States,
1 - A Forecast Driven Model For Prepositioning Supplies In
Preparation For A Hurricane
Gina Galindo, University of Del Norte,
Rajan Batta
We present a forecast-driven dynamic model for prepositioning relief items in
preparation for a foreseen hurricane. The decisions in our model are based on
real-time updated information from periodic forecast advisories issued by the
National Hurricane Center (NHC). Our approach, which combines Decision
Theory and stochastic programming, determines the time to start prepositioning,
and the units to be prepositioned at each selected supply point. It also accounts
for the possible re-positioning of already prepositioned supplies. Our results show
that our model outperforms the alternative wait-and-see approach.
2 - Modeling Proactive Surgery Cancellation With Weather
Forecast Updates
Mahsa Ghanbarpour Mamaghani, Northeastern University,
Boston, MA, 02148-8208, United States,
, Ozlem Ergun
Severe weather such as hurricanes and snowstorms can dramatically disrupt the
delivery of many essential services within a community, including healthcare
services. This research introduces proactive surgeries cancellation planning due to
snowstorms with considering weather forecast updates. Since the snowstorms can
be predicted more accurate in the last steps of planning horizon the problem is
formulated as an evaluation of the tradeoff between more accurate forecasts and
cost of late cancellations for determining optimal surgeries cancellation.
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Music Row 1- Omni
Emerging Trends in Business Innovation
Sponsored: Technology, Innovation Management &
Entrepreneurship
Sponsored Session
Chair: Fangyun Tan, Southern Methodist University, 6212 Bishop Blvd,
Dallas, TX, 75275, United States,
1 - Impact Of Tabletop Technology On Restaurant Performance
Fangyun Tan, Southern Methodist University,
Serguei Netessine
We analyze a large data set of transactions in a casual restaurant chain to
understand the effect of implementing a tabletop technology on service
performance (measured in sales and meal duration). We find the technology
directly increases sales and significant reduces the meal duration. We provide
insights on how to manage technology in restaurant operations.
2 - The Role Of Surge Pricing On A Service Platform With
Self-scheduling Capacity
Kaitlin Daniels, Assistant Professor, Olin Business School,
Washington University in St. Louis, St Louis, MO, United States,
Platforms like Uber use dynamic pricing policies to manage a workforce of “self-
scheduling” providers who decide for themselves how often to work. We show
that the optimal dynamic pricing policy substantially increases the platform’s
profit relative to contracts with a fixed price or fixed wage (or both) and although
surge pricing (which pays providers a fixed percentage of a dynamic price) is not
optimal, it generally achieves near optimal profit. Furthermore, we find that
providers and consumers are generally better off with surge pricing because
providers are better utilized and consumers benefit both from lower prices during
normal demand and expanded access to service during peak demand.
3 - Team Leadership And Performance: Combining The Roles Of
Direction And Participation
Morvarid Rahmani, Georgia Institute of Technology, 800 West
Peachtree Street, NW, Atlanta, GA, 30308-1149, United States,
Uday Karmarkar,
Guillaume Roels
One of the challenges that project team leaders face is how to combine their roles
as individual contributors and managers. In this paper, we propose a model of
team leadership and study how a contributor leader should adjust her managing
effort over time and with respect to the project characteristics (e.g., team
members’ incentives and team size).
4 - Sole Inventor Vs Team Of Inventors: What’s Best?
Tian Chan, Emory University, Atlanta, GA, United States,
, Jurgen Mihm, Manuel Sosa
Should a team of inventors outperform individual inventors in creating
groundbreaking innovations? The empirical evidence that examines into scientific
papers and technology patents (representing millions of inventive work) suggests
that the answer is an unqualified “yes”. However, in this work we use design
patent data to show that “teams are better than individuals” is not true in the
context of design innovation. While so, we find that collaboration yields future
dividends—designers who has collaborated extensively in the past but currently
operates alone outperforms either teams or sole designers. We discuss the
implications of our results in the organization of innovative work.
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Music Row 2- Omni
Meet the Editors of Service Science
Sponsored: Service Science
Sponsored Session
Chair: Paul Maglio, University of California, Merced,
School of Engineering, Merced, CA, 95343, United States,
In this session, the editors of INFORMS Service Science will discuss the mission
and state of the journal and answer questions.
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Music Row 3- Omni
Modeling and Optimization for Renewable Energy
Integration
Sponsored: Service Science
Sponsored Session
Chair: Jian Guo, Western New England University, Western New
England University, Springfield, MA, 01119, United States,
Co-Chair: Zhaojun Li, Western New England University,
Western New England University, Springfield, MA, United States,
1 - Impact Of Future Wind Power Scenarios On The Distributionally
Robust Operation And Cost Of Reserves
Bita Analui, Post Doctoral Scholar, Ira A. Fulton Schools of
Engineering, Arizona State University, Tempe, AZ, 85287-9309,
United States, Anna Scaglione
The increasing share of renewable energy and its intermittency have led to new
challenges in modeling and optimization of power system operations. In this
work, we present the distributionally robust extension of multistage stochastic
optimization of reserves operations under stochastic wind power generation. In
this setting, the reference probability model is a scenario tree based on the direct
quantization of wind power trajectories. Constructing the alternative scenario
trees in the epsilon-neighborhood of the reference tree forms the ambiguity set P,
wherein an iterative algorithm determines the minimax solution and identifies
the worst case probability model.
2 - The Quest For Zero-carbon Supply Chain: An Onsite
Generation Approach
Tongdan Jin, Texas State University,
Is it feasible to deploy a zero emission production-logistics system using
intermittent renewable energy? If so, how to design such eco-friendly supply
chain system in a distributed generation environment? In this talk we present a
wind- and solar-based onsite generation system to achieve carbon-neutral
performance for a multi-facility production-distribution network with affordable
cost.
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