Building Mathematical Models for Multicriteria and Multiobjective Applications 2017

Full text

Editorial
Building Mathematical Models for Multicriteria and
Multiobjective Applications 2017
Adiel Teixeira de Almeida ,1Love Ekenberg ,2,3 Juan Carlos Leyva Lopez ,4
and Danielle Costa Morais 1
1Department of Management Engineering, Universidade Federal de Pernambuco, Recife, PE, Brazil
2International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, 2361 Laxenburg, Austria
3Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden
4Department of Economic and Management Sciences, Universidad Aut´
onoma de Occidente, Culiac´
an, SIN, Mexico
Correspondence should be addressed to Adiel Teixeira de Almeida; almeida@cdsid.org.br
Received 1 March 2018; Accepted 4 March 2018; Published 22 April 2018
Copyright © 2018 Adiel Teixeira de Almeida et al. is is an open access article distributed under the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
is special issue has been requested by developers of the
publisher based on the success of “Building Mathematical
Models for Multicriteria and Multiobjective Applications
2016.” As a result, this special issue is one of the publisher’s
Annual Special Issues. at is, it is the rst issue in a
seriesofspecialissueswhichwillbepublishedeachyear.
ItishopedthatsuchaserieswillattracttheMCDM/A
community and have a long-term impact on researchers
and practitioners alike, particularly on those interested in
building mathematical decision models for applications in
real or realistic situations.
erefore, this special issue addresses decision prob-
lems involving multiple criteria, which may be conict-
ing and explicitly incommensurable. Multicriteria decision-
making/aid (MCDM/A) and multiobjective methods can
be highly useful for decision-makers (DMs) in such tasks.
A large number of high-quality papers were submitted for
consideration in this special issue. Aer a rigorous peer-
review process, thirteen papers were accepted (an acceptance
rate of around 20%). ey cover and discuss a variety of appli-
cations for real-world problems, while combining theoretical
methodology and mathematical analysis. e authors of these
papers are active in dierent countries around the world,
namely, Brazil, Mexico, Canada, China, India, Pakistan, and
Spain.
In the eld of supplier selection, four papers are presented
that deal with dierent methodologies and problems in that
context. Q. Pang et al. propose a method that integrates
fuzzy set theory and grey relational analysis (a fuzzy-grey
approach) in order to select a green supplier in a low-carbon
supplychain.Basedonthedemandofcompaniesinalow-
carbon supply chain, 4 main criteria and 22 subcriteria are
established for selecting a green supplier.
R. Krishankumar, S. Ravichandran, and R. Ramprakash
present a computational framework for cloud vendor selec-
tion by proposing IVIF-ELECTRE (IVIFE), an interval val-
ued intuitionistic fuzzy (IVIF) environment based on ELEC-
TRE method. is proposal was formulated and integrated
with the popular TOPSIS method so as to obtain a linear
ranking. e practicality of the proposed framework is
demonstrated by using a supplier selection example while its
strength is made apparent by comparing it with other similar
methods.
E. A. Frej et al. developed a decision model for solving a
supplier selection problem in a food industry by conducting
preference modeling using a exible and interactive elicita-
tion technique with the decision-maker (DM), aided by the
FITradeo method. FITradeo DSS also provides graphical
visualization for the DM at each step in a exible way, so
that the DM can holistically analyze the performance of the
potentially optimal alternatives.
X. Sun puts forward a max-max model to facilitate
selecting the optimal combination of suppliers. e paper
presents an analytical model that describes the synergies
Hindawi
Mathematical Problems in Engineering
Volume 2018, Article ID 4986197, 2 pages
https://doi.org/10.1155/2018/4986197

2Mathematical Problems in Engineering
between components of a product and supplier selection
criteria that enhance the eectiveness of supplier selection.
To enhance air trac control, F. Tello et al. present a mul-
tiobjective perspective on a scheduling problem regarding the
work-shis of air trac controllers (ATC). is approach,
given a xed number of ATCs and an airspace sector to cover,
optimizes several objectives. ese are to do with ATC duties,
rest periods, and positions; the structure of the solution; the
number of control center changes, or the distribution of ATC
workloads, while satisfying a set of ATC working conditions
set out in Spanish regulation.
Still using the multiobjective perspective, Y. Yang et al.
propose a new multiobjective optimization design method,
which combines a support vector regression (SVR) surro-
gate model and a nondominated sorting genetic algorithm
(NSGA-II), in order to undertake the multiobjective opti-
mization of the location and layout of xtures of sheet metal
parts (SMP) and to reduce the excessive cost of computing
ne element analysis (FEA) during the iterative optimization.
e authors illustrate the proposed method by locating and
xingthelayoutoftheskinofanaircrafuselage.
Astotheproblemofplanningtheresponsetoand
recovery from a disaster, L. B. Cavalcanti, A. B. Mendes,
andH.T.Y.Yoshizakiproposeamethodofhowtoimprove
planning for delivering cargo in the aermath of a disaster
by using value-focused thinking (VFT) and the SMARTER
method. VFT was applied to elucidate the objectives of deliv-
ering cargo to disaster victims during response operations
andtocreatesolutionalternatives.SMARTERmethodwas
applied to evaluate the alternatives; in this case, strategies for
planning the delivery of aid to disaster victims.
For the problem of product selection, S. Latif et al. intro-
duce the optimum selection of the next forwarder vehicle
(NFV) which is used to disseminate data in a vehicular ad
hoc network (VANET) using the analytical network process
(ANP). e NFV is selected on the basis of three parameters,
namely, direction, position and distance. is paper also
presents a mathematical model to compute the priorities of
vehicles within a network.
As to the construction sector, C. C. G. Fam´
aandL.A.
Alencar put forward a model for classifying managers by
competencies, using the NeXClass method in order to match
each manager to the position that is the most appropriate for
them based on assessing their competencies and performance
on construction projects to date. is model can be useful not
only for those responsible for selecting managers but also for
theemployeewhoaspirestobeamanager.
H. Liang, S. Zhang, and Y. Su develop a composite index
to measure the multidimensional concept of industrialization
eciency in prefabricated residential buildings, by applying
the fuzzy analytic hierarchy process (fuzzy AHP) and the
fuzzy technique for order preference by similarity to ideal
solution (fuzzy TOPSIS), thereby combining the hierarchical
structures of indicators into one overall index.
X.-Z.Zheng,F.Wang,andJ.-L.Zhoudevelopthehuman
factors analysis and classication system (HFACS) frame-
work to deal with a hydropower project construction for
evaluating faulty behavior risk (FBR) of high-risk operations
using ANP and evidence theory.
Dealing with joint methodologies, A. Frini proposes
multicriteria intelligence aid (MCIA) which extends multi-
criteria decision aid (MCDA) to the context of analyzing
intelligence. e MCIA steps consist of (i) structuring the
competitor/threat decision problem, (ii) handling imperfect
data, (iii) modeling the analyst’s attitude towards risk, and
(iv) aggregating the performance of the potential actions
generated. An example of its application is provided based on
a military context.
N.Rangel-Valdezetal.setoutanddiscusstherobustness
of a preference-disaggregation analysis (PDA) metaheuristic
method to estimate the parameters for a model of an
outranking-based relational system of preferences. is pro-
posal presents a method for analyzing the robustness of PDA
strategies that work with the complete set of the parameters of
the ELECTRE III model. e method is considered robust if
the solutions obtained in the presence of noise can maintain
the same performance in predicting preference judgments
in a new reference set. e research shows experimental
evidence that the PDA method keeps the same performance
in situations with up to 10% of noise level, thus making it
robust.
Despite the signicant spread of MCDM/A methods, the
variety of applications discussed in this special issue can
only cover a small diversity of contexts in which they might
be applied. e papers demonstrate the extensive range of
contexts over which these methods can be used and we hope
that they will prompt and encourage readers to contribute
towards further developments in building MCDM/A models
in the future.
Acknowledgments
We would like to express our deepest gratitude to the authors
for their contributions to this special issue and the coopera-
tionandassistanceofmanyreviewers,whosefeedbackwas
very useful in improving the quality of papers submitted.
Also, we record our genuine gratitude to other editors of
the editorial board for their cooperation by coordinating the
editorial process for those contributions in which one of the
Editors of this special issue was a co-author.
Adiel Teixeira de Almeida
Love Ekenberg
Juan Carlos Leyva Lopez
Danielle Costa Morais