Informs 2015

122 / 552

INFORMS Philadelphia – 2015
120
SD02
02-Room 302, Marriott
OR and Homeland Security 1: Data Driven Decisions
Cluster: Homeland Security
Invited Session
Chair: Paul Kantor, Prof, Rutgers, 96 Frelinghuysen Dr,
Piscataway, NJ, United States of America,
1 - Detecting and Locating GPS Jamming
Jeff Coffed, Senior Marketing Manager, Exelis Inc., 400 Initiative
Drive, Rochester, NY, 14606, United States of America,
Joe Rolli
GPS has become a ubiquitous service supporting critical infrastructure. Its signal is
susceptible to service blockages due to jamming. Recognizing this threat, Exelis
set out to develop technology that identifies and locates jamming sources. The
system can be located around high-risk areas to instantaneously sense and locate
jamming sources. Users will receive pin-point geolocation information in order to
respond. We will share information about the threat, the technology and test
results.
2 - Walk through Metal Detectors at Sports Stadiums
Christie Nelson, Postdoctoral Associate, CCICADA, Rutgers
University, 96 Frelinghuysen Rd, 4th Floor, CoRE Building,
Piscataway, NJ, United States of America,
, Paul Kantor, Fred Roberts,
Dennis Egan, Brian Ricks, Michael Tobia, Brian Nakamura,
Ryan Whytlaw, Michael Young
Experimental designs are presented for walk through metal detectors (WTMDs) in
stadium settings. Experiments were created to understand how WTMDs perform
in real settings, typically outdoors, as opposed to idealized indoor lab scenarios.
Experiments were then carried out at sports stadiums. Because of the large
number of experimental factors involved, a combinatorial experimental design
approach was taken.
3 - A Differential Privacy Mechanism for Graph Problems Protecting
Confidential Network Data
William Pottenger, Rutgers University, 96 Frelinghuysen Road,
CoRE Building, Piscataway, NJ, 08854, United States of America,
Kunikazu Yoda
Graph problems are important for homeland security since most critical
infrastructure such as a power grid can be modeled by a graph. Such network
data often contains highly sensitive information and a publically released
summary must not give hints to terrorists who might exploit the data in
developing targets. We present a differential privacy mechanism for graph
problems whose solutions reveal useful global information while not revealing
significant confidential individual information.
4 - Fusion Learning by Individual-to-Clique (FLIC): Efficient Approach
to Enhancing Individual Inference
Minge Xie, Professor, Rutgers University, 501 Hill Center,
Piscataway, United States of America,
Learning from multiple studies can often be fused together to yield a more
effective inference. We present a new approach, named “Fusion Learning by
Individual-to-Clique (FLIC)”, to enhancing inference of an individual study
through adaptive combination of confidence distributions obtained from its clique
(namely similar studies). Drawing inference from the clique allows borrowing
strength from similar studies to enhance the inference. It can also substantially
reduce computational expense.
5 - The Unaccompanied Alien Children Challenge: Applying Queuing
Theory to Improve Logistics in Immigration
Javier Rubio-Herrero, Rutgers University, Piscataway, NJ,
United States of America,
The recent wave of unaccompanied alien children that crossed the border of the
United States posed a very important logistic challenge for the US DHS and US
DHHS. In this presentation, Queuing Theory is presented as an option to forecast
the performance of facilities aimed at carrying pre-screenings of these immigrants
before their final placement in shelters. We present a mathematically tractable
queuing model, illustrate its capabilities, and discuss opportunities that this
approach offers.
SD03
03-Room 303, Marriott
Application of Scheduling Theory
Cluster: Scheduling and Project Management
Invited Session
Chair: Zhixin Liu, University of Michigan-Dearborn, 19000 Hubbard
Drive, Dearborn, MI, United States of America,
1 - Optimization Based Production Scheduling with Batching
Lixin Tang, Professor, Northeastern University, Institute of
Industrial Engineering and, Logistics Optimization, Shenyang,
110819, China,
We discuss the production scheduling problems with batching decision arising
from steel, petrochemical and non-ferrous metal industry. For general problems,
complexity and optimal solution properties are analyzed; polynomial time
algorithm for solvable cases, and approximation algorithm with theoretical
analysis for NP-hard problems are proposed. For complicated problems, row-
column generation algorithm, LR&CG based dual algorithm, and improved
Benders decomposition algorithm are proposed.
2 - An Optimization Model for Loan Collection
Ping He, Zhejiang University, 866 Yuhangtang Rd, Hangzhou,
China, , Zhongsheng Hua, Zhixin Liu
This paper studies how to make efficient collection decisions over consumer term-
loan accounts. Since a loan’s onset, an account experiences state transition across
ages. We model the state transition of loan accounts using a Markov transition
matrix, and provide optimization method to determine the collection action at
each state and age for each consumer type that maximizes the lender’s expected
value. Managerial insights and general rules for consumer loan collection are
recommended.
3 - Two-Agent Scheduling on a Single P-Batching Machine with
Equal Processing Time and Non-Identical Job
Jun-Qiang Wang, Professor, Northwestern Polytechnical
University, Box 554, No. 127 West Youyi Road, Department of
Industrial Engineering, Xi’an, 710072, China,
Cheng-wu Zhang, Yingqian Zhang,
Guo-qiang Fan, Joseph Leung
We schedule two agents on a single parallel-batching machine. For the linear
weighted sum model, we presented an approximation algorithm and analyze the
absolute/asymptotic worst-case ratio. For the restriction model, no approximation
algorithm with a finite bound exists, unless P = NP. We propose two polynomial-
time heuristic algorithms using two restriction-solving strategies. For the
non-domination model, we define a boundary of Pareto-optimal set. The
proposed heuristics outperform NSGA-II.
4 - Vessel and Containing Planning in Feeder Lines
Yu Wang, PhD Candidate, Dept. of IELM, HKUST, Rm 5567,
Academic Building, Clear Water Bay, Kowloon, 999077,
Hong Kong - PRC, , Xiangtong Qi
We consider the vessel and container planning problem in feeder lines. A feeder
vessel sequentially visits n ports, collecting containers from each port and
transporting to hub port. The route of the vessel is pre-defined. The optimal
serving policy for the vessel to load and unload under stochastic demand is
investigated. The process is described as a Markov decision process, which aims to
maximize the expected revenue. Furthermore, the optimal loading and unloading
policy is derived.
SD04
04-Room 304, Marriott
Special Panel on 20th Year Anniversary of WORMS:
Strategies for Advancing Women in OR/MS
Sponsor: Women in OR/MS
Sponsored Session
Chair: Guzin Bayraksan, Associate Professor, The Ohio State University,
Integrated Systems Engineering, Columbus, OH, 43209, United States
of America,
1 - Special Panel on 20th Year Anniversary of WORMS:
Strategies for Advancing Women in OR/MS
Moderator:Guzin Bayraksan, Associate Professor, The Ohio State
University, Integrated Systems Engineering, Columbus, OH,
43209, United States of America, , Panelists:
Laura Mclay, Margarit Khachatryan, Paula Lipka, Candace Yano
This special panel will look back at the 20 years of Women in OR/MS. Then, it
will focus on strategies for advancing women in OR/MS. Topics include how to
recruit and retain women students and faculty in Operations Research and
Management Science, academic and industrial leadership.
SD02