Technical Sessions – Monday July 11

1 - Alpha-returns to Scale in Production Technology with
Variable Returns to Scale
Sara Zeidani, Mathematics Dept., Science and Research Branch,
Islamic Azad University, Tehran-Sadeghieh-Bolvar
Ferdos-Shirpur Street- Unit 20, 1477893855, Tehran, Iran,
Islamic Republic Of, sara.zeidani@gmail.com, Mohsen
Rostamy-Malkhalifeh, Farhad Hosseinzadeh Lotfi
In this paper, we discuss about strictly increasing and decreasing returns to
scale then homogeneous production technology and its relationship with alphareturns
to scale was introduced. The definition of alpha-returns to scale with
variable returns to scale has been evaluated (BCC model). After that new assumption
and theorems are proposed and proved.
2 - A New Mixed Integer Linear Model for Technology Selection
Ali Asghar Foroughi, Mathematics Dept., Qom University,
3716146611, Qom, Iran, Islamic Republic Of,
aa_foroughi@yahoo.com
In many applications of data envelopment analysis, it is desirable to select the
best decision making units. In this paper a new mixed integer linear model is
proposed to provide a single efficient decision making unit for technology selection.
The relation between the approach and some existing methods are discussed,
and it is shown that the proposed approach can overcome some drawbacks
of the other methods. The contents of the paper are illustrated by several
numerical examples
3 - Cost Efficiency by Data Envelopment Analysis with
Nonlinear Virtual Input and Output
Razieh Mehrjoo, Science and Research Branch, Islamic Azad
University, 1477893855, Tehran, Iran, Islamic Republic Of,
mikhakf@yahoo.com, Gholam Reza Jahanshahloo, Mohsen
Rostamy-Malkhalifeh
A method for measuring the efficiency of decision making units (DMUs) is
Data Envelopment Analysis (DEA). An underlying assumption in DEA is that
the weights coupled with the ratio scales of the inputs and outputs imply linear
value functions. In this paper we represent a model to measure cost efficiency
for these models. To this end we give minimal cost modelfor nonlinear virtual
outputs and inputs in a piece-wise linear fashion. The applicability of the proposed
model is in the some real evaluating programs that are with nonlinear
virtual outputs and inputs.
4 - Efficiency Prediction in Decision Making Units Merger
using Data Envelopment Analysis and Neural Network
Vahid Behbood, Information Technology, University of
Technology Sydney, 2007, Sydney, NSW, Australia,
vbehbood@it.uts.edu.au, Jie Lu
Overall efficiency of the system is one of the most important factors which
determines the success of merging Decision Making Units (DMUs) in the system.
In a successful merger, the inputs of DMUs are mixed together to produce
enhanced outputs which improve the system efficiency. Hence, prediction the
system efficiency prior to merger can significantly support policy makers to decide
and judge appropriately. This study develops an approach to predict the
system efficiency which will be changed as result of merger. The proposed approach
applies Data Envelopment Analysis (DEA) to compute the efficiency of
DMUs in the system based on their inputs and outputs. Afterward the Neural
Network is used to learn the relationship between the inputs, outputs and efficiency
of DMUs and consequently predicts the overall system efficiency. The
prediction approach is validated using commercial banks data and the empirical
results indicate its outstanding performance and its ability as an effective and
accurate approach for finance industry.
� FB-19
Friday, 13:15-14:45
Meeting Room 216
Telecommunications
Stream: Network Optimisation and Telecommunications
Contributed session
Chair: Raymundo Oliveira, Mathematics Institute, Federal University
of Rio de Janeiro, Rua Leopoldo Miguez, 144 apt 901, Copacabana,
22060-020, Rio de Janeiro, RJ, Brazil,
raymundo.oliveira2010@gmail.com
IFORS 2011 - Melbourne FB-20
1 - Optimization Algorithms for the Automatic Planning of
Hybrid Access Telecommunication Networks
Anderson Parreira, DSSO, Fund. CPqD, 13086902, Campinas,
SP, Brazil, parreira@cpqd.com.br, Sandro Gatti, Guilherme
Telles, Rivael Penze
Network access planning can be stated as the problem of finding minimal cost
sets of equipments and cables connecting offer and demand points in order
to provide services (video, data and voice). As literature shows, this kind of
problems is NP-hard. Our approach combines shortest paths algorithms and
heuristics in graphs and phylogenetic tree reconstruction to create a network.
To evaluate the algorithm we performed a set of experiments on real infrastructure
data. Data sets are georeferenced and offer and demand points include
bandwidth. The experiments have shown that the algorithm builds good network
concerning cost and also visual layout.
2 - Covering a Region in Telecommunication
Raymundo Oliveira, Mathematics Institute, Federal University of
Rio de Janeiro, Rua Leopoldo Miguez, 144 apt 901, Copacabana,
22060-020, Rio de Janeiro, RJ, Brazil,
raymundo.oliveira2010@gmail.com, Angela Goncalvez
We consider the problem of covering a region with circles. We seek to position
m antennas in a flat region with n locations (X,Y) to be covered by the antennas.
Each location will be covered by the nearest antenna. It is necessary to locate
the m antennas in order to minimize the longest distance antenna-location. This
reduces to a MinMaxMin problem. The paper presents a new methodology, using
Nelder-Mead method, which solves a nonlinear problem in a space with
dimensions 2m. A set of computational results illustrate its performance.
3 - Line Graph Tranformations for Minimum Cost Euler
Tour with Movement Prohibition
Marcos José Negreiros, MESTRADO PROFISSIONAL EM
COMPUTAÇÃO, UNIVERSIDADE ESTADUAL DO CEARÁ,
Av Paranjana, 1700 - Campus do Itaperi, 60740-000, Fortaleza,
CEARÁ, Brazil, negreiro@graphvs.com.br, Augusto Palhano
This work investigates a new procedure based on Line Graph Transformation,
for solving the problem of performing Euler Tour with movement prohibitions.
Previous literature consider the problem as a step forward to design comfortable
Euler tours for garbage collection vehicles by using heuristics. We show new
exact and metaheuristics methods for this problem and report results obtained
from real life garbage collection networks.
� FB-20
Friday, 13:15-14:45
Meeting Room 217
Multi-criteria Decision Analysis
Stream: Contributed Talks
Contributed session
Chair: Pekka Leskinen, Research Programme for Production and
Consumption, Finnish Environment Institute, Joensuu, Finland,
pekka.leskinen@ymparisto.fi
1 - An Integrated Mathematical Optimisation Framework
for Suppliers Ranking and Demand Allocation
Shabnam Mojtahedzadeh Sarjami, Mathematics and Statistics,
Curtin University of Technology, Kent St, Bentley WA, 6102,
Perth, Western Australia, Australia,
Shabnam.mojtahed@postgrad.curtin.edu.au, Louis Caccetta
The supplier selection problem is to determine a portfolio of suppliers from a
set of candidates that best meets the requirement of an organisation. In this
paper an integrated mathematical optimisation framework is developed to effectively
rank the suppliers and allocate the demand. This framework ranks
the suppliers under conflicting criteria with often varying criteria importance.
Then, through an optimisation model the demand is allocated to the ranked
suppliers.
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