Informs 2015

194 / 552

INFORMS Philadelphia – 2015
192
MB60
60-Room 111A, CC
Cases in the Undergraduate OR Curriculum
Sponsor: INFORM-ED
Sponsored Session
Chair: Michael Veatch, Gordon College, 255 Grapevine Rd, Dept. of
Mathematics, Wenham, MA, 01984, United States of America,
1 - Strategies for using Cases in the Undergraduate Classroom
Matthew Drake, Associate Professor Of Supply Chain
Management, Duquesne University, 925 Rockwell Hall, 600
Forbes Avenue, Pittsburgh, PA, 15282, United States of America,
Students often develop a better understanding of quantitative material by
applying the analytical techniques to realistic decision scenarios. Cases provide
OR/MS instructors with an effective vehicle to introduce applications of business
analytics in practice. While they are common at the graduate level, cases are not
used as often with undergraduates. In this session we will discuss strategies for
using cases effectively with undergraduate students.
2 - On the Development of Case Studies for an Undergraduate
Business Analytics Course
Eric Huggins, Professor Of Management, Fort Lewis College,
1000 Rim Drive, Durango, CO, 81301, United States of America,
Over the past three years I have developed half a dozen case studies for an
undergraduate business analytics course. Each case study started as a big data set
with a few objectives attached to it, and with the help of my students, they have
evolved into current (for now), relevant (I think), interesting (I hope) OR-related
case studies.
3 - Where Do I Find Classroom Cases?
James Cochran, Professor Of Applied Statistics And The Rogers-
spivey Faculty Fellow, University of Alabama, P.O. Box 870226,
Tuscaloosa, AL, 35487-0226, United States of America,
Many OR/analytics instructors want to incorporate short cases into their
undergraduate courses but have difficulty finding suitable, relevant, and topical
cases. Where can an instructor find such cases? If s/he is willing to experiment
with writing cases, s/he can find the bases of cases in the news, popular culture,
and her/his own life (and perhaps publish their efforts in INFORMS Transactions
Today). We will demonstrate through several examples from the speaker’s
experience writing cases.
4 - Teaching Undergraduate Analytics using Cases
Peter Bell, Ivey Business School at Western University,
1255 Western Road, London, ON, N6G 0N1, Canada,
, Mehmet Begen, Fredrik Odegaard
Ivey’s undergraduate analytics courses have used cases extensively for many
years. This interactive presentation will discuss some of the benefits (and costs) of
a case-based approach to undergraduate teaching.
MB61
61-Room 111B, CC
Stochastic and Robust Optimization Models in
Electric Power Systems
Sponsor: ENRE – Energy I – Electricity
Sponsored Session
Chair: Andy Sun, Assistant Professor, Georgia Institute of Technology,
755 Ferst Drive, Atlanta, GA, 30332, United States of America,
1 - Two-stage Distributionally Robust Unit Commitment with
Generalized Linear Decision Rules
Yuanyuan Guo, University of Michigan, 1205 Beal Ave., Ann
Arbor, MI, 48109, United States of America, ,
Ruiwei Jiang, Jianhui Wang
It is challenging to accurately estimate the joint probability distribution of the
renewable energy. In this paper, based on a small amount of marginal historical
data, we propose a two-stage distributionally robust unit commitment model that
considers a set of plausible probability distributions. This model is less
conservative than classical robust unit commitment models and more
computationally tractable by using generalized linear decision rules.
2 - Stochastic Unit Commitment with Topology Control Recourse for
Renewables Integration
Jiaying Shi, University of California, Berkeley, CA,
United States of America, United States of America,
Shmuel Oren
We introduce a two stage stochastic unit commitment formulation in which the
second stage recourse actions include possible reconfiguration of the transmission
grid through line switching. Switching action in the second stage are determined
by a heuristic method. Such topology control capability can mitigate adverse
variability in realized renewables output and improve unit commitment
efficiency.
3 - Multistage Robust Unit Commitment with Dynamic
Uncertainty Sets
Alvaro Lorca, Georgia Tech, 251 10th St. NW Apt. A622, Atlanta,
GA, 30318, United States of America,
We present a multistage robust unit commitment model with renewables and
storage using a simple but effective affine policy for dispatch decisions, while
considering dynamic uncertainty sets that integrate wind and solar power
resources taking into account spatial and temporal correlations. Our solution
algorithm contains enhancements that allow solving the resulting problem
efficiently. We also present simulation experiments to evaluate the benefits of our
approach.
4 - Multi-stage Stochastic Unit Commitment with SDDP
Jikai Zou, Graduate Research Assistant, Georgia Institute of
Technology, 755 Ferst Dr. NW, Atlanta, GA, 30332, United States
of America, Shabbir Ahmed, Andy Sun
Despite the great amount of research, stochastic unit commitment (UC) problems,
where binary commitment decisions adapt to uncertainty with a multi-stage
structure, still remain one of the most challenging stochastic programming
problems. In this paper, we investigate a sampling based algorithm that combines
stochastic dual dynamic programming (SDDP) and the integer L-shaped method
for solving multistage stochastic UC. Numerical results and algorithmic
improvement will be discussed.
MB62
62-Room 112A, CC
Optimization Approaches for Invasive Species and
Pest Management
Sponsor: ENRE – Environment I – Environment and Sustainability
Sponsored Session
Chair: Esra Buyuktahtakin, Assistant Professor, Wichita State
University, 1845 N Fairmount, Wichita, KS, 67260, Wichita, United
States of America,
1 - Optimal Inspection of Imports to Prevent Invasive
Pest Introduction
Robert Haight, USDA Forest Service, Northern Research Station,
St. Paul, MN, United States of America,
Rebecca Epanchin-niell, Cuicui Chen
Based on our work with USDA-APHIS, we study an acceptance sampling problem
that incorporates several features of quality control in public safety programs,
including the simultaneous inspection of many heterogeneous lots, a budget
constraint that limits inspection, inspection error, and an objective of minimizing
cost to consumers. We apply our results to inspecting live plant imports to prevent
invasive pest introduction.
2 - Cost-effective Planning of Invasive Species Surveillance with the
Maximum Expected Coverage Concept
Denys Yemshanov, Research Scientist, Natural Resources Canada,
Canadian Forest Service, Great Lakes Forestry Centre, 1219
Queen Street East, Sault Ste Marie, ON, P6A2E5, Canada,
, Robert Haight,
Frank Koch, Bo Lu, Jean Turgeon, Ronald Fournier
We present two invasion survey models based on the maximum expected
coverage principle (MECP). The models maximize the expected number of
invaded sources that are covered by the surveys, where a source is covered if at
least one of its transmission pathways connects to a surveyed destination. We
present one- and two-stage models designed to survey invasive forest pests in
Canada and the U.S. Overall, the approach provides flexible solution to survey
the long-distance spread of invasive pests.
MB60