Systems, Man & Cybernetics - April 2017 - 53

research areas are in human factors,
cognitive engineering, and humanintegrated systems engineering.
Steven J. Landry (slandry@isye
.gatech.edu) earned his Ph.D. degree
from the H. Milton Stewart School of
Industrial and Systems Engineering
at the Georgia Institute of Technology
(Georgia Tech), Atlanta, in 2004. He is
currently an associate professor and
associate head in the School of Industrial Engineering at Purdue University,
West Lafayette, Indiana. He specializes in the area of human factors and air
transportation systems engineering.
Dr. Landry's research interests are in
air traffic management and control,
flight-deck displays, aviation alerting
systems, human-computer interfaces
for complex systems, formal symbolic
frameworks for human factors, statebased modeling of complex sociotechnical systems, procedure design, and
visual perception and eye tracking.

A New Consensus Model
for Group Decision-Making
Problems with Non-Homogeneous
Experts
Group decision ma k i ng (GDM )
consists of multiple indiv iduals
interacting to reach a decision. Usually, two processes are necessary to
solve GDM problems: a consensus
process and a selection process. The
consensus process is used to reach
a final solution with a certain level
of agreement among the experts. It
is a dynamic and iterative process,
composed of several rounds where
the experts express, discuss, and
modify their preferences. On the
other hand, the selection process
uses all individual preferences to
obtain a collective solution.
To achieve a high consensus level
among the experts, it is useful to
provide the whole group of experts
with some advice (feedback information) on how far the group is from
consensus, what the most controversial issues (alternatives) are, which
preferences are in the highest disagreement with the rest of the group,
how their change would influence
the consensus degree, and so on. In

Judging is based on
originality; technical
merit; potential
impact to the IEEE
Systems, Man, and
Cybernetics Society
fields of interest; and
presentation quality.

the literature, we find that the consensus models proposed for GDM
problems are guided by consensus
degrees, similarity measures, and/or
consistency measures.
When we work in heterogeneous
GDM frameworks, we have importance degrees associated with the
experts by expressing their different knowledge levels on the problem.
Usually, the importance degrees are
applied in the weighted aggregation
operators developed to solve the
decision situations.
In our paper, we study another
application possibility, i.e., the use of
heterogeneity existing among experts
to guide the consensus model. Thus,
the main goal of the paper is to present a new consensus model for heterogeneous GDM problems guided
also by the heterogeneity criterion. It
is also based on consensus degrees
and similarity measures, but it presents a new feedback mechanism
that adjusts the amount of advice
required by each expert depending
on his or her own relevance or importance level.
About the Authors
Ignacio Javier Pérez Gálvez (ignaciojavier.perez@uca.es) earned his M.Sc.
and Ph.D. degrees in computer science from the University of Granada,
Spain, in 2007 and 2011, respectively.
He is currently a professor of computer science with the Department of
Computer Engineering, University of
Cádiz, Spain.
Francisco Javier Cabrerizo
(cabrerizo@decsai.ugr.es) earned his
Ap ri l 2017

M.Sc. and Ph.D. degrees in computer
science from the University of Granada, Spain, in 2006 and 2008, respectively. He is currently an associate professor in the Department of Computer Science and Artificial In telligence at
University of Granada, Spain. He is an
associate editor for Journal of Intelligent and Fuzzy Systems and a member of the editorial board of Journal of
Universal Computer Science.
Sergio Alonso (zerjioi@ugr.es)
earned his M.Sc. degree in computer
science in 2003 and his Ph.D. degree
in 2006, where he specialized in
decision making with incomplete
information. He is an associate professor in the Software Engineering
Department at the University of
Granada, Spain.
Enrique Herrera-Viedma (viedma@
decsai.ugr.es) earned his Ph.D. degree
in computer science from the University of Granada in 1996. He is a full professor in computer science of the Deptartment of Computer Science and
Artificial Intelligence, University of
Granada, Spain. He has served as vicedean of Research and Technology in
Library Science School, and he currently is vice president for Research
and Knowledge Transfer in University
of Granada.
The 2016 IEEE SMC Franklin
V. Taylor Memorial Award
The IEEE SMC Franklin V. Taylor
Memorial Award is presented annually to recognize the best effective oral
presentation and paper at the previous calendar year's SMCS conference.
Judging is based on quality and technical merit. The prize consists of US$500
and a plaque funded by the SMCS. The
winners for 2016 are George Bucsan,
Michael Balchanos, Dimitri N. Mavris,
Jae Seung Lee, Masanori Ishigaki, and
Atsushi Iwai. A portion of their winning paper is presented next.

Management of Technologies for
Electric Vehicle Efficiency
Toward Optimizing Range
(MOTEVETOR)
Heating, ventilation, and air-conditioning (HVAC) systems control is

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