[PDF] ALIO Back Matter

SA13
3 - Uncertainties in Corporate Greenhouse Gases Inventory:
Methodology and Applications
Gutemberg Brasil, UFES, Av. Fernando Ferrari, 514, Departamento
de Estatística, Vitória, 29075-910, Brazil, ghbrasil@terra.com.br,
Paulo António de Souza Júnior, João Andrade de Carvalho Júnior
Corporate inventories of greenhouse gas emissions, as well as the biomass stock,
contain relevant information for the decision makers at the private sector to support
their policies related to climate change. A methodology for the calculation of
emissions from processes and services is presented. This methodology includes the
expressions of uncertainties associated to the calculation of greenhouse gas
emissions. The importance of the knowledge of these uncertainties is also discussed.
4 - The Efficiency of Preventive Maintenance Planning and the
Multicriteria Methods: A Case Study
Carlos Enrique Escobar-Toledo, Professor, National University of
Mexico (UNAM), Circuito Institutos. Facultad de Química,
Conjuntos D-E Room 310, Mexuco, 04510, Mexico,
carloset@servidor.unam.mx, Edgar Sevilla Juarez
The goal of this work considers process plants reliability to manage failure risks
trough preventive maintenance. We propose the ranking of equipment according
with a set of appropriate criteria for a better preventive maintenance planning,
considering that it, is multicriterio by nature. To show how the methodology works,
naphtha Hidrodesulfurating process plant is used as a case study. The results shows
process equipment ranking to give preventive maintenance under budget
constraints.
5 - Comprehensive Indicators of Sustainable Development
Viktorija Bojovic, Teaching Assistant, Faculty of Economics,
9-11 Segedinski put, Subotica, 24000, Serbia-Montenegro,
vbojovic@uns.ac.rs
The concerns about accurate measure of long-term economic sustainability have
resulted in myriad of indexes and specific measures. The necessity to reduce
information overload of incomparable numbers by proliferating comprehensive
indicators of sustainable development is paramount. Presenting possibilities of
reducing information overload through generation of more relevant information for
integrative long-term environment and economic planning and decision making is
the purpose of the paper.
■ SA14
Aula 365- Third Floor
Game Theory and Data Mining
Cluster: Game Theory and its Applications
Invited Session
Chair: Richard Weber, Professor, University of Chile, Republica 701,
Santiago, Chile, rweber@dii.uchile.cl
1 - Strategic Costs in a Specific Location Mechanism to NIMBY
Fernando Alexis Crespo Romero, Santiago, RM, Chile,
facrespo@gmail.com
NIMBY (Not In My Backyard) are facilities that are necessary to society, but rejected
by communities that have to host them. We revised a mechanism for location
decisions using auctions over costs declared by communities. This mechanism hasn’t
the ideal conditions, but it maintains the ranking of true costs. For this mechanism
we calculate the declared strategic costs for communities and compare our results
with other classical results of strategic declarations in auctions mechanism.
2 - Sequential Equilibria Algorithms for Adversarial Data Mining with
Signaling Games
Gaston L`Huillier, University of Chile, Republica 701, Santiago, Chile,
glhuilli@dcc.uchile.cl, Richard Weber, Nicolas Figueroa
In adversarial classification with signaling games, the equilibria finding problem is
directly related to the performance of the classifier. However, equilibria refinements
in incomplete information games has been widely recognized as a complex
procedure. For this, different algorithms for the learning process of the strategic
interaction between agents are proposed, improving the classifier’s performance and
obtaining promising results in a phishing fraud detection environment.
3 - Game Theory - Data Mining Model for Price Dynamics in
Financial Institutions
Cristian Bravo, PhD Candidate, University of Chile, Republica 701,
Santiago, Chile, cbravo@dii.uchile.cl, Richard Weber,
Nicolas Figueroa
We present a two-stage model consisting on a hybrid support vector machines -
neural network model to estimate market share (demands) for competing
companies at a client level. The demands serve as input for a game theoretic model,
which considers the strategic relationships between costs and demands when the
companies decide prices. An application to real-life data provided useful insights
about cost structures, the competitive behavior of the institutions, and the behavior
of the customers.
ALIO / INFORMS International – 2010
26
■ SA15
Aula 351- Third Floor
Data Mining for Decision Making I
Sponsor: Data Mining: Knowledge Discovery and
Data Mining for Decision Making
Sponsored Session
Chair: Louis Duclos-Gosselin, Applied Mathematics (Predictive Analysis,
Data Mining) Consultant at Sinapse, Sinapse & INFORMS Data Mining
Section, 1170 Boul. Lebourgneuf, Bureau 320, Quebec, QC, G2K2E3,
Canada, louis.gosselin@hotmail.com
1 - Inference in Large Dynamic Networks
Shawndra Hill, Assistant Professor of Operations and Information
Management, The Wharton School of the University of
Pennsylvania, Philadelphia, PA, 19104, United States of America,
shawndra@wharton.upenn.edu
Telecommunications and social-network sites such as MySpace, Friendster and
Facebook record data on explicit social networks. Online advertising firms are now
linking these explicit networks to actions such as clicks and purchases. We combine
explicit social network and purchase data to predict business outcomes. We find that
explicit social network data are useful for predicting purchase above models that
rely only on traditional attributes like demographics and geography.
2 - Information-theoretic Approach to Data Mining
Behlul Caliskan, Research Assistant at Marmara University,
Marmara University, Faculty of Communication, Nisantasi Campus,
Sisli / Istanbul, Turkey, behlul.caliskan@marmara.edu.tr
Because a database may be considered as a statistical population, and an attribute as
a statistical variable taking values from its domain, data mining tasks may be
approached using information-theoretic techniques. Many information-theoretic
measures have been proposed and applied to quantify the importance of attributes
and relationships between them. In this paper, the information-theoretic techniques
used applied DM tasks will be analyzed and some recent applications will be
mentioned.
3 - Predictive Analysis (Data Mining) Implementation: Predicting Fraud
in E-Commerce Transaction Data
Louis Duclos-Gosselin, Applied Mathematics (Predictive Analysis,
Data Mining) Consultant at Sinapse, Sinapse & INFORMS Data
Mining Section, 1170 Boul. Lebourgneuf, Bureau 320, Quebec, QC,
G2K2E3, Canada, louis.gosselin@hotmail.com
Starting from earlier e-commerce management sciences studies, managers have
always tried to find better techniques to effectively manage e-commerce operations
in order to reduce the costs while increasing customers’ satisfaction. This paper
shows how managers can use predictive analysis to address fraud detection
problems. A new predictive analysis technique for solving problems related to fraud
detection is presented. The technique has been tested on two web transaction
anomaly data.
■ SA16
Aula 385- Third Floor
Heuristics
Contributed Session
Chair: Claudia Fink, Universidade de São Paulo - USP, Av. Trabalhador
São-carlense, 400, São Carlos, SP, 13560-970, Brazil,
claudiaf@icmc.usp.br
1 - Improving Service Level of the Public Safety: A Proposal Based on
Tabu Search and p-median Model
Rodrigo Ferreira, UFRN, Caixa Postal 1551, Lagoa Nova, Natal, RN,
59078-970, Brazil, rodjpf@gmail.com, Dario Aloise, André Gurgel
Criminality is a relevant problem to be dealt by public safety systems. This work
proposes a model to support police units allocation. This model combines p-median
model and travelling salesman problem to define regions, travel distance and
operational cost. It aims enhance coverage, reduce operational costs and increase
service level.
2 - Heuristics Based on LB and VNS to Solve Lot Scheduling
Formulations for the Beverage Production
Deisemara Ferreira, Federal University of São Carlos, Rua Chicrala
Abrahao, 320, São Jose do Rio Preto, Brazil, deise@dep.ufscar.br,
Reinaldo Morabito
In this work we applied heuristics based on local branching, VNS and other
strategies to solve formulations of lot sizing and scheduling problems, in the
beverage industry. The results are compared to solutions in the literature, as well as,
an actual production scheduling of a company.