IEEE Computational Intelligence Magazine - February 2021 - 10

computation, and Tulane University had
faculty who worked on evolutionary
computation. Evidently, this was not a
random choice. One of the reasons for
deciding to work with Alan was because
I had already done some work with him
in robotics (after two failed attempts to
find a research topic with other faculty
members who worked in Programming
Languages and Natural Language Processing) during my Master's study. Alan
proposed me some possible PhD thesis
topics that sounded interesting to me
(e.g., one of them involved developing a
programming language for robotics).
After reading heavily about these topics
(and even taking some extra courses), I
decided that I didn't want to write my
PhD thesis in robotics. However, I liked
Alan since he was young and friendly,
and I was his first PhD student. I realized that this would give me some freedom regarding my thesis topic, which
was something that looked much more
difficult to achieve with the faculty
members who had done some work on
evolutionary computation since they
were already full professors. This decision had obvious consequences from
which the main one was that I had to
choose my PhD topic without any help.
After some days, I realized that this was

harder than I thought. However, one
day, I started talking with Prof. Bill
Buckles, who worked on evolutionary
algorithms. I asked him if he knew of
some interesting topic in which I could
do my PhD work. Prof. Buckles immediately suggested me to work on multiobjective optimization. He said that this
was an important topic and that few
people were interested in working on it.
At that time, I didn't even know what
multi-objective optimization meant, but
I started looking up information about
this topic and I soon got excited about
it. Looking this in retrospective, I can say
that I was very lucky, because at that
time there were indeed very few people
interested in this area (now called Evolutionary Multi-Objective Optimization
(EMOO)) and my early start combined
with a series of other fortunate events
defined the research path that led to the
place where I am today. Needless to say,
I will always be grateful to Prof. Buckles
for his valuable advice which was another major event in my career.
The fourth major event was moving
to the Centro de Investigación y de Estudios Avanzados del Instituto Politécnico
Nacional (CINVESTAV-IPN) located in
Mexico City in January 2001. This was a
major event in my academic career after

FIGURE 1 The first generation of members of EVOCINV. From left to right, back to front: Margarita Reyes Sierra, Adriana Lara López, Carlos A. Coello Coello, Nareli Cruz Cortés, Ricardo
Landa Becerra, Efrén Mezura Montes, Gregorio Toscano Pulido and Eduardo Serna Pérez.

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | FEBRUARY 2021

having short-term appointments in other
institutions in UK, USA and Mexico.
CINVESTAV-IPN is the most prestigious public research center in Mexico
and has a work philosophy heavily
-oriented towards excellence in research.
However, one of its peculiar aspects is
that it can grant degrees without the
need of an agreement with a University.
Nevertheless, since it is a research center
rather than a University, it only offers
graduate degrees. Therefore, the teaching
load is quite low (normally 2 courses in
one year, each having only a handful of
students). Additionally, the high reputation of CINVESTAV-IPN tends to
attract very talented graduate students
who are highly motivated to do research.
Needless to say, working at CINVESTAVIPN has been fundamental for my academic career, not only because of the
very talented students that I have had the
opportunity to supervise but also for the
strong institutional support that I have
received during all these years.
2. Can you tell us a little bit about
your research work that brought
you to this appointment?

As indicated before, since 1994 I decided that I would work on a field that is
now known as EMOO. For my PhD
thesis, I decided to work on a topic that
was novel at that time: the hybridization
of evolutionary algorithms with mathematical programming techniques. While
writing my PhD thesis, I learned a lot
about evolutionary algorithms (although
I never took a formal course on this
topic other than the Artificial Intelligence course that I mentioned before),
about mathematical programming techniques and about the little work that
had been done so far on EMOO. However, since the multi-objective evolutionary algorithms (MOEAs) that I
proposed in my PhD thesis were based
on nonlinear aggregating functions
instead of Pareto optimality (which was
starting to become popular at that time),
I had problems to publish them in evolutionary computation conferences and
journals. I realized that I had to move
towards the development of Paretobased MOEAs to get accepted by this

IEEE Computational Intelligence Magazine - February 2021

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