Informs 2015

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INFORMS Philadelphia – 2015
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5 - Minimizing Automotive Supply Chain Costs under Mixed
Transportation Modes
Sherif Masoud, Operations Research Analyst, RockTenn,
3950 Shackleford Rd., Duluth, MN, United States of America,
, Scott Mason
We present an industry-motivated integrated production and transportation
problem focused on short-term automotive supply chain planning. We consider
multiple, heterogeneous modes of transportation that offer a cost vs. delivery time
option to the manufacturer. Computational results demonstrate the efficiency of a
proposed metaheuristic-based solution approach, given the problem’s NP-hard
computational complexity.
MB79
79-Room 302, CC
Software Demonstration
Cluster: Software Demonstrations
Invited Session
1 - AMPL - Developing Optimization Applications Quickly and
Reliably with Algebraic Modeling
Robert Fourer, President, AMPL Optimization Inc., 2521 Asbury
Ave, Evanston, IL, 60201, United States of America,
Can you negotiate the complexities of the optimization modeling lifecycle, and
deliver a working application before the problem owner loses interest? Algebraic
languages were invented to streamline the key steps of model formulation,
testing, and revision. Today they are supported by powerful facilities for
embedding models into larger systems and deploying them to users. This
presentation introduces algebraic modeling for optimization through examples
using classic and recently introduced features of the AMPL language and system.
2 - Gurobi Optimization, Inc. – Modeling with the Gurobi
Python Interface
Renan Garcia, Optimization Support Engineer, GAMS
Development Corp
Are you looking for an environment that combines the expressiveness of a
modeling language with the power and flexibility of a programming language?
The Gurobi Python interface allows you to build concise and efficient
optimization models using high-level modeling constructs. Moreover, Python
itself has a vast ecosystem of packages designed to increase your productivity,
such as a notebook-style interface (iPython Notebook), data access capabilities
and web development tools. This tutorial will provide an overview of these
features, including detailed examples that show how to use the Python interface
to build models that can be turned into full optimization applications.
Monday, 12:30pm - 2:30pm
Exhibit Hall A
Monday Poster Session
Contributed Session
Chair: Wenjing Shen, Drexel University, Philadelphia, PA,
United States of America,
Co-Chair: Allen Holder, Rose-Hulman Mathematics, Terre Haute, IN,
United States of America,
Co-Chair: Min Wang, Drexel University, 3141 Chestnut Street,
Philadelphia, PA, United States of America,
1 - Big Data
Marwah Halwani, University of North Texas, 2812 Loon Lake
Road, Denton, TX, 76210, United States of America,
Victor Prybutok, Adam Corwin,
Daniel Peak
The Big Data Model developed to provide a foundation for the proper use of Big
Data and Data Visualization in Social Media environments that will drive positive
bottom-line results. This research addresses how can Big Data represented with
Data Visualization in a Social Media environment contribute to better decisions
2 - Brightness-location Congruency Effects on Consumer Behavior
in Retail Context
Tsutomu Sunaga, Professor, Kwansei Gakuin University, 1-1-155,
Uegahara, Nishinomiya, Hyogo, 662-8501, Japan,
, Jaewoo Park
The study investigates the effects of the crossmodal correspondence between
colour and visual heaviness on consumer purchase behavior. The results of the
experiments demonstrate that brightness-location congruence, specifically
products with bright (dark) colour at the higher (lower) shelf positions, increases
shoppers’ perceptual fluency and promotes their purchase behaviour.
3 - A Kalman Filter Algorithm for Artillery Firing Shift
Michael Bendersky, Ben Gurion University of the Negev,
Beersheba, Israel, , Israel David
We propose an innovative algorithm for artillery firing shift using the Kalman
Filter approach. Firing shift implies an immediate artillery engagement of a target
(“fire for effect”) without a prior fire adjustment (by a forward observer). The
capability of firing shift provides undeniable operational advantages.
Implementing the Kalman Filter allows sequential fire adjustment relying on
multiple auxiliary targets.
4 - Demand Forecasting and Area Marketing for Gas Appliances
Kosuke Shaku, Tokyogas, 1-5-20,Kaigan, Minato-ku, Tokyo,
Japan,
Tokyo gas has been utilizing O.R. to a lot of fields such as marketing, emergency
response, and so on. Demand Forecasting of gas appliances has been a big
problem for gas appliances sales. We managed to establish the method of
quantitatively rational demand forecast by utilizing the CRM data of appliances
stocks, survival analysis, and transience of appliances types in replacement. The
result of this work has been adopted to many Tokyo gas measures such as sales
goal setting and area marketing.
5 - Who to Call Predictive Modeling of Potential Customers Based
on Customer Behavior Data
Lin Shi, Kihihi Network Information Systems Technology, China,
A telemarketing campaign is operated in a classified advertisements website
A model is needed to predict the possibility of customers order and
then those with highest possibility can be selected. The paper designed and
implemented a practical decision support system which could generate and
distribute customer lists to sales representative. The poster introduces the object,
business background, specific aims, modeling procedures, modeling data, final
result and the conclusions of the work. Four techniques have been used to
compare the performance. Random forest gives the best result. The final dynamic
model integrates customers online behavior data, which is also called click-stream
data as indicators of willingness to pay. The result from field study inspired that in
the future work, we may push dynamic modeling for more robust and precise
prediction.
6 - The Opportunity Cost of Federal Subsidies for Electricity
Generation in the U.S.
James Gibson, USMC, 2414 Turtle Bay Dr, New Bern, NC, 28562,
United States of America,
This study is the first investigation of the opportunity cost associated with electric
utility sector federal subsidies using the mean-variance portfolio theory. The
application of portfolio theory provides for an examination of how policy
decisions influence electricity generation costs. The results indicate federal
subsidies have an uncertain effect on electricity generation costs and the
associated tax burden becomes an opportunity cost assumed by society and
individual taxpayers.
7 - The Effect of Shape and Semantic Novelty in Product
Design Usage
Harris Kyriakou, Stevens Institute of Technology, 1 Castle Point
on Hudson, Hoboken, NJ, 07087, United States of America,
Our study examines 35,727 product designs submitted to the largest 3D printing
online community from January 2009 to June 2013, showing how (i) shape
novelty, (ii) semantic novelty and (iii) their interaction affect product design
usage. We develop both a shape-based and a text-based measure of novelty by
identifying designs that are dissimilar to any preexisting design.
8 - Who Wants My Product? Affinity-based Marketing
Leyla Zhuhadar, Assistant Professor, Western Kentucky
University, 1906 College Heights Blvd, Grise Hall, Bowling Green,
KY, 42101, United States of America,
In this research, we have developed a marketing application for data mining with
the goal of publicizing a new product to those customers with a high affinity for
it. We assembled suitable data to test and evaluate different mining algorithms on
it. We have used the buyers of our product of interest as “model customers” for
finding similar customers among the non-buyers. Finally, we deployed our final
model to our customer base.
9 - Robust Security-constraint Unit Commitment with
Dynamic Rating
Anna Danandeh, University of South Florida, Tampa, FL, 33613,
United States of America, , Bo Zeng,
Brian Buckley
A challenge in UC is the impact of uncertain factors such as ambient temperature
on generation and transmission capacities. Since system capacity is mostly
determined statically, weather changes can cause outages and/or congestions. We
developed a 2 stage robust security-constraint UC formulation which dynamically
rates the assets and hedges against possible efficiency drops. Leveraging the
correlation between weather and load, it yields a less conservative decision and a
faster computation.
POSTER SESSION