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EC-DIGEST-L  January 2021

EC-DIGEST-L January 2021


EC-Digest v35n2


Eric 'Siggy' Scott <[log in to unmask]>


Evolutionary Computation Digest <[log in to unmask]>


Sat, 30 Jan 2021 12:36:45 -0500





text/plain (688 lines)

Evolutionary Computation Digest — Saturday, 30 January 2021, Volume
35: Issue 2

SUBMISSION ADDRESS:    [log in to unmask]

(UN)SUBSCRIPTION INSTRUCTIONS:  at the bottom of this email

Today's Topics:

 - Immediate: Research Internship Position opened in Optimization at
IRIMAS Institute
- 05 March: Metaheuristics Summer School (MESS2020+1)

 CFPs (with submission deadline)
 - 30 January: International Conference on Swarm Intelligence (ICSI'2021)
 - 31 January: IEEE CEC Special Session on Representation Learning
meets Meta-heuristic Optimization
 - 05 February (Extended): International Conference on Optimization
and Learning (OLA'2021)
 - 07 April: EvoStar Call for Participation
 - 12 April: GECCO Workshop on Parallel and Distributed Evolutionary
Inspired Methods
 - 12 April: GECCO Workshop on NeuroEvolution at Work
 - 30 June: CfP: Applied Sciences special issue on "Application of
Evolutionary Computation"


April 7–9, 2021, Seville, Spain: EvoStar 2021

July 10–14, 2021, Lille, France: GECCO 2021

Sender: Julien Lepagnot <[log in to unmask]>
Subject: Research internship position opened in optimization at IRIMAS institute

Please find, below, links to an offer (in english and in french) of a
postgraduate internship position to be filled as soon as possible:

Feel free to forward this offer.

With best regards,

Associate professor in computer science
Université de Haute-Alsace - Institut IRIMAS (EA 7499)
12 rue des Frères Lumière, 68093 Mulhouse
Tel : +33 3 89 33 60 28

Sender: Mario Pavone <[log in to unmask]>
Subject: MESS 2020+1 ~ Learning & Optimization from Big Data ~ 15-18 June 2021

Call for Participation (apologies for multiple copies)

MESS 2020+1 - Metaheuristics Summer School
- Learning & Optimization from Big Data -
15-18 June 2021, Catania, Italy
(virtual and onsite mode)
[log in to unmask]

** APPLICATION DEADLINE: 5th March 2021 **

MESS 2020+1 is aimed at qualified and strongly motivated MSc and PhD
students; post-docs; young researchers, and both academic and
industrial professionals to provide an overview on the several
metaheuristics techniques, and an in-depth analysis of the
state-of-the-art. The main theme of this edition is ?Learning and
Optimization from Big Data?, therefore MESS 2020+1 wants to focus on
(i) Learning for Metaheuristics; (ii) Optimization in Machine
Learning; and (iii) how Optimization and Learning affect the
Metaheuristics making them relevant in handling Big Data.

Participants will be delivered a certificate of attendance indicating
the number of hours of lectures (36-40 hours of lectures). In
according to the academic system all PhD and master students attending
to the summer school will may get 8 ECTS points.


+ Paolo Arena, Unviersity of Catania, Italy
      Lecture#1: TBA
      Lecture#2: TBA

+ Angelo Cangelosi, University of Manchester & Alan Turing Institute, UK
      Lecture#1: Cognitive and Developmental Robotics, part 1
      Lecture#2: Cognitive and Developmental Robotics, part 2

+ Swagatam Das, Indian Statistical Institute, Kolkata
      Lecture#1: Deep Generative Adversarial Networks and Their
Application to Class-imbalanced Learning
      Lecture#2: Non-convex Constrained Optimization - Some Advanced Approaches

+ Luca Maria Gambardella, IDSIA Istituto Dalle Molle for Artificial
Intelligence, Switzerland
      Lecture#1: TBA
      Lecture#2:  TBA

+ Salvatore Greco, University of Catania, Italy & University of Portsmouth, UK
      Lecture#1: TBA
      Lecture#2: TBA

+ Giuseppe F. Italiano, Luiss University, Italy
      Lecture#1: TBA
      Lecture#2: TBA

+ Rafael Martì, University of Valencia, Spain
      Lecture#1: Optimization in Graph Drawing
      Lecture#2: Models and Heuristics in Discrete Diversity Maximization

+ Gabriela Ochoa, University of Stirling, UK
      Lecture#1: Fitness Landscape Analysis
      Lecture#2: Complex Networks in Search and Optimisation

+ Mauricio Resende, AMAZON, USA
      Lecture#1: GRASP with Path-Relinking for Real-World Optimization Problems
      Lecture#2: Biased Random-Key Genetic Algorithms with Applications

+ El-Ghazali Talbi, University of Lille 1, France
      Lecture#1: Machine learning for metaheuristics
      Lecture#2: Automated design of deep neural networks

+ Daniele Vigo, University of Bologna, Italy
      Lecture#1: Fast and scalable heuristics for vehicle routing problems
      Lecture#2: Integrating machine learning into vehicle routing heuristics


All participants to the school will be involved in the ?Metaheuristics
Competition?, where each of them will must develop a metaheuristic
solution on the given problem. The top three of the competition
ranking will receive the MESS 2020+1 prize. Students whose algorithm
will rank in the top ten of the competition ranking will be invited to
submit a manuscript of their work to be published in the special
volume MESS 2020+1 of the AIRO Springer Series.


All participants may submit an abstract of their recent results, or
works in progress, for presentation and having the opportunities for
debate and interact with leaders in the field. Mini-Workshop
Organizers and Scientific Committee will review the abstracts and will
recommend for the format of the presentation (oral or poster). All
abstracts will be published on the electronic hands-out book of the
summer school.

The Abstracts must be submitted by *March 5, 2020*.

*See Previous Edition - MESS 2018*

** MORE INFORMATION:  --   [log in to unmask]
Facebook Group:

Sender: [log in to unmask]
Subject: The Twelfth International Conference on Swarm Intelligence (ICSI'2021)

ICSI'2021: Call for Papers (Jan. 30, 2021)

Name: The Twelfth International Conference on Swarm Intelligence (ICSI'2021)
Dates: July 17-21, 2021
Location: Qingdao, China

Important Dates:

Jan. 30, 2021: Deadline for Paper Submission.

Brief Description:

The Twelfth International Conference on Swarm Intelligence (ICSI'2021)
serves as one of most important Swarm Intelligence Forum worldwide for
researchers and practitioners to exchange latest advantages in
theories, technologies, and applications of swarm intelligence and
related areas. The ICSI'2021 is the twelfth annual event in this
high-reputation ICSI series after successful eleven previous events.
Papers presented at the ICSI'2021 will be published by Springer-Nature
in Lecture Notes in Computer Science (indexed by EI Compendex, ISTP,
DBLP, SCOPUS, Web of Science ISI Thomson, etc.), some high-quality
papers will be selected for SCI-indexed Transaction and Journal
(including IEEE Trans, IASEI Trans. Swarm Intelligence, IJSIR, Swarm
and Evolutionary Optimization, International Journal of Intelligent
System, Electronics, etc.).

Sponsored and Co-sponsored by International Association of Swarm and
Evolutionary Intelligences, Peking University, Southern University of
Science and Technology and Ocean University of China. Technically
Co-sponsored/supported by IEEE Computational Intelligence Society,
IEEE Beijing Chapter, World Federation of Soft Computing,
International Neural Network Society, Springer-Verlag, etc.(more to be

The ICSI 2021 will be held in Ocean University of China, Qingdao which
is the beautiful and biggest coast city of Shandong province,
China,and is a vibrant city, surprising in its diversity and rich in
its history and culture.

Welcome to you and your team members as well as your colleagues to
submit your/their latest proposals to our upcoming ICSI'2021! We are
looking forward to your presence at ICSI'2021 in the Beatiful Qingdao
of China.

ICSI'2021 Secretariat
Email: [log in to unmask]

Sender: Peter Korosec <[log in to unmask]>
Subject: CfP reminder: CEC 2021 Special session on Representation
Learning meets Meta-heuristic Optimization (RepL4Opt)


The Special Session on

        Representation Learning meets Meta-heuristic Optimization (RepL4Opt)

at the 2021 IEEE Congress on Evolutionary Computation (CEC 2021) in
Kraków, Poland, June 28 - July 1, 2021 welcomes submissions of original
research articles on all aspects of Representation Learning relevant to
optimization with evolutionary algorithms and related approaches.

Accepted papers will be part of the IEEE CEC Proceedings.
Submission deadline: January 31, 2021
Important: Make sure to select the RepL4Opt special session (SS-57)
when submitting!


Per-instance automated algorithm selection and configuration techniques
 use high-level information about the problem instance to train
meta-models that aim to predict which algorithm or  which configuration
works well on this particular instance.  Per-instance selection and
configuration have shown promising  performances for a number of
classical optimization problems, including  SAT solving, AI planning,
etc. In the context of black-box  optimization, properties of the
instance need to be inferred from samples.  Key design questions in
this context concern  the selection of meaningful features to quantify
the instance,  the efficient computation of these features, the  number
of samples required to obtain reliable approximations, the
distribution of these samples, the possibility to use algorithms’
trajectory data for feature computation, and many more. Research
addressing these questions is subsumed under the term “exploratory
landscape analysis” (ELA). In ELA, a large number of different features
 have been proposed, which raise up the need of feature selection,
since  many features can be highly correlated and have a decremental
impact on  understanding of the underlying recommendations. This is
where  representation learning comes into play. Representation learning
has  its most important applications in machine learning, where bias
and  redundancies in data can have severe effects on performance. It
focuses  on methods that automatically learn new data representations
(i.e.,  feature engineering) using the raw data needed to improve the
performance of machine learning tasks. Representation learning methods
are also successfully used to reduce the dimension of the data, via
automatically detecting correlations.

In this special session, we are particularly interested in studying how
representation learning can contribute to improve performance and to a
better understanding of ELA-based analyses, e.g., by automatically
reducing bias, correlations and redundancies in the feature data.


We welcome submissions on the following topics:
- Representation learning techniques for structured, unstructured, and
graph data
- Exploratory landscape analysis (ELA) for feature engineering of the
landscape space
- Feature selection, ranking and sensitivity analysis
- Sensitivity analysis of sampling techniques applied in ELA
- Representation learning applied on landscape data
- Representation learning applied on performance data
- Improving understanding of data (landscape and/or performance)
through visualization techniques
- Landscape data representation in automatic algorithm selection and
- Performance data representation in automatic algorithm selection and
- Machine learning for automatic algorithm selection and configuration
- Meta-learning
- Transfer of approaches between machine learning and optimization
- Taxonomies/ontologies for describing the algorithm instance space
- Complementary analysis of different benchmarking datasets
- Any other topic relating representation learning to sampling-based


All submissions should follow the CEC2021 submission guidelines
provided at IEEE CEC 2021 Submission Website
( Special
session papers are treated the same as regular conference papers.
Please specify that your paper is for the Special Session on RepL4Opt:
Representation Learning meets Meta-heuristic Optimization (SS-57). All
papers accepted and presented at CEC 2021 will be included in the
conference proceedings published by IEEE Explore.

In order to participate to this special session, full or student
registration of CEC 2021 is needed.


- Paper submission: 31 January 2021
- Paper acceptance notification: 22 March 2021
- Final paper submission: 7 April 2021
- Conference: 28 June - 1 July 2021

Sender: El-ghazali Talbi <[log in to unmask]>
Subject: Extended deadline OLA'2021 @Sicilia Italy

           International Conference on Optimization and Learning
                           21-23 June 2021
                       Catania (Sicilia), Italy

OLA is a conference focusing on the future challenges of optimization
and learning methods and their applications. The conference OLA'2021
will provide an opportunity to the international research community in
optimization and learning to discuss recent research results and to
develop new ideas and collaborations in a friendly and relaxed atmosphere.

OLA'2021 welcomes presentations that cover any aspects of optimization
and learning research such as big optimization and learning,
optimization for learning, learning for optimization, optimization and
learning under uncertainty, deep learning, new high-impact applications,
parameter tuning, 4th industrial revolution, computer vision,
hybridization issues, optimization-simulation, meta-modeling,
high-performance computing, parallel and distributed optimization and
learning, surrogate modeling, multi-objective optimization ...

Submission papers: We will accept two different types of submissions:
-       S1: Extended abstracts of work-in-progress and position papers
of a maximum of 3 pages
-       S2: Original research contributions of a maximum of 10 pages

Important dates:

Paper submission deadline     Extended to Feb 05, 2021
Notification of acceptance    March 24, 2021

Proceedings: Accepted papers in categories S1 and S2 will be published
in the proceedings. A SCOPUS and DBLP indexed Springer book will be
published for accepted long papers. All proceedings will be available at
the conference.

Sender: "João Nuno Correia" <[log in to unmask]>
Subject: EvoStar 2021 - The Leading European Event on Bio-Inspired
Computation - Online 7-9 April 2021

Call for participation for the EvoStar conference

Conference: 7 to 9 April 2021.
Venue: *ONLINE*
All accepted papers will be printed in the proceedings published by
Springer Verlag in the Lecture Notes in Computer Science (LNCS) series.


- EvoStar goes online-only!
Evo* 2021 will be an online-only event.
Please help us keep it as the friendly & familiar event it has always been!
Send us your thoughts for better networking and exchange of ideas to
[log in to unmask]

Sender: Antonio Della Cioppa <[log in to unmask]>
Subject: ACM GECCO Workshop CfP: Parallel and Distributed Evolutionary
Inspired Methods @GECCO 2021

Dear Colleagues,
we would like to inform you about the forthcoming ACM Workshop on
Parallel and Distributed Evolutionary Inspired Methods within GECCO
to be held in Lille, France, July 10-14, 2021.

Note that GECCO 2021 will be an electronic-only conference due to
COVID-19. It will be required that the presentation of all
accepted papers is provided in the form of a pre-recorded talk. More
details about this will be provided soon together with how workshop
discussions will occur.

Nature inspired methods include all paradigms of evolutionary
computation such as genetic algorithms, evolution strategies, genetic
ant algorithms, particle swarm systems and so on.
These methods are being more and more frequently used to face
real-world problems characterized by a huge number of possible
thus their execution often requires large amounts of time. Therefore,
they can highly benefit from parallel and distributed implementations,
in terms of both reduction in execution time and improvement in
quality of the achieved solutions.
The workshop aims at creating a forum of excellence on the use of
parallel models of evolutionary computation methods. This can be
by bringing together for an exchange of ideas researchers from a
variety of different areas, ranging from computer scientists and
on the one hand to application-devoted researchers like biologists,
chemists, physicians on the other hand.
Since we are going to increasingly observe a trend towards
parallelization of evolutionary models in next years, not only will a
Workshop on
this topic be of immediate relevance, it will also provide a platform
for encouraging such implementations.
Researchers putting emphasis on parallel issues in their work with
evolutionary systems, are encouraged to submit their work. This event
the ideal place for informal contact, exchange of ideas and
discussions with fellow researchers.
The scope of the workshop is to receive high-quality contributions on
topics related to parallel and distributed versions of evolutionary
ranging from theoretical work to innovative applications in the
context of (but not limited to):

- Theoretical and experimental studies on parallel and distributed
model implementations (population size, synchronization, homogeneity,
  communication, topology, speedup, etc.)
- New trends in parallel and distributed evolutionary computation
including Grid and Cloud Computing, Internet Computing, General
  Computation on Graphics Processing Units (GPGPU), multi-  core
architectures and supercomputers
- New parallel and distributed evolutionary models
- Parallel and distributed implementation of evolutionary-fuzzy,
evolutionary-neuro and evolutionary-neuro-fuzzy hybrids
- Development of parallel and distributed evolutionary algorithms for
data mining on big data and machine learning
- Parallel and distributed multi-objective evolutionary algorithms
- Real-world applications of parallel and distributed evolutionary algorithms

Each paper submitted will be rigorously evaluated in a double-blind
review process. The evaluation will ensure high interest and expertise
of the reviewers.
Review criteria include significance of the work, technical soundness,
novelty, clarity, writing quality, and sufficiency of information to
permit replication,
if applicable. All accepted papers will be published in the ACM Digital Library.
More detailed information, together with a more comprehensive list of
application domains, is available at:


- Paper Submission deadline: April 12, 2021
- Notification of paper acceptance: April 26, 2021
- Camera ready submission: May 3, 2021
- Author registration deadline: TBA
- Conference dates: July 10th-14th, 2021

Sender: Antonio Della Cioppa <[log in to unmask]>
Subject: ACM GECCO Workshop CfP: NeuroEvolution at Work @GECCO 2021

Dear Colleagues,
we would like to inform you about the forthcoming ACM Workshop on
NeuroEvolution at Work within GECCO 2021, to be held in
Lille, France, July 10-14, 2021.


In the last years, inspired by the fact that natural brains themselves
are the products of an evolutionary process, the quest for evolving
and optimizing artificial neural networks through evolutionary
computation has enabled researchers to successfully apply
to many domains such as strategy games, robotics, big data, and so on.
The reason behind this success lies in important capabilities
that are typically unavailable to traditional approaches, including
evolving neural network building blocks, hyperparameters,
architectures and even the algorithms for learning themselves (meta-learning).
Although promising, the use of neuroevolution poses important problems
and challenges for its future developments. Firstly, many of its
paradigms suffer from lack of parameter-space diversity, meaning with
this a failure in providing diversity in the behaviors generated by
the different networks. Moreover, the harnessing of neuroevolution to
optimize deep neural networks requires noticeable computational
power and, consequently, the investigation of new trends in enhancing
the computational performance.
NEWK@Work workshop aims:

- to bring together researchers working in the fields of deep
learning, evolutionary computation and optimization to exchange new
  about potential directions for future research;
- to create a forum of excellence on neuroevolution that will help
interested researchers from a variety of different areas, ranging from
  computer scientists and engineers on the one hand to
application-devoted researchers on the other hand, to gain a
high-level view
  about the current state of the art.

Since an increasing trend to neuroevolution in the next years seems
likely to be observed, not only will a workshop on this topic be of
immediate relevance to get an insight in future trends, it will also
provide a common ground to encourage novel paradigms and applications.
Therefore, researchers putting emphasis on neuroevolution issues in
their work are encouraged to submit their work. This event is also
the ideal place for informal contacts, exchanges of ideas and
discussions with fellow researchers.
The scope of the workshop is to receive high-quality contributions on
topics related to neuroevolution, ranging from theoretical works to
innovative applications in the context of (but not limited to):

- theoretical and experimental studies involving neuroevolution on
machine learning in general, and on deep and reinforcement learning in
- development of innovative neuroevolution paradigms
- parallel and distributed neuroevolution methods
- new search operators for neuroevolution
- hybrid methods for neuroevolution
- surrogate models for fitness estimation in neuroevolution
- applications of neuroevolution to Artificial Intelligence agents and
to real-world problems

More detailed information, together with a more comprehensive list of
application domains, is available at:


- Paper Submission deadline: April 12, 2021
- Notification of paper acceptance: April 26, 2021
- Camera ready submission: May 3, 2021
- Author registration deadline: TBA
- Conference dates: July 10th-14th, 2021

Sender: Federico Divina <[log in to unmask]>
Subject: CfP: Special issue on "Application of Evolutionary Computation"

Call for Papers

Special Issue on "Application of Evolutionary Computation"

A special issue of Applied Sciences (IF 2.474 ISSN 2076-3417).
This special issue belongs to the section "Computing and Artificial

Deadline for manuscript submissions: 30 June 2021.
Guest Editors
Federico Divina and Francisco A. Gómez Vela
(Pablo de Olavide University - Spain)

Dear Colleagues,

Evolutionary Computation has been applied to a wide range of real-life
problems, ranging from telecommunication networks to complex systems,
finance and economics, games, image analysis, evolutionary music and
art, parameter optimization, bioinformatics, scheduling, and

The aim of this Special Issue is to present a collection of studies
describing the latest advances in techniques and applications of
Genetic Algorithms, Evolution Strategies, Evolutionary Programming,
Genetic Programming, Simulated Annealing, Ant Colony Optimization, and
related techniques. Of particular interest is the application of these
techniques to computationally difficult combinatorial problems.

We also encourage researchers to share their original work in the
field of computational analysis of gene expression data. Topics of
primary interest include, among others, the applications of:

genetic algorithms;
evolution strategies;
evolutionary programming;
memetic algorithms;
genetic programming;
ant colony optimization;
co-evolutionary algorithms;
artificial immune systems;
particle swarm optimization; and
classifier systems.
evolutionary computation;
soft computing;
real-life applications.

Prof. Dr. Federico Divina
Prof. Dr. Francisco A. Gómez Vela
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering
and logging in to this website. Once you are registered, click here to
go to the submission form. Manuscripts can be submitted until the
deadline. All papers will be peer-reviewed. Accepted papers will be
published continuously in the journal (as soon as accepted) and will
be listed together on the special issue website. Research articles,
review articles as well as short communications are invited. For
planned papers, a title and short abstract (about 100 words) can be
sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor
be under consideration for publication elsewhere (except conference
proceedings papers). All manuscripts are thoroughly refereed through a
single-blind peer-review process. A guide for authors and other
relevant information for submission of manuscripts is available on the
Instructions for Authors page. Applied Sciences is an international
peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a
manuscript. The Article Processing Charge (APC) for publication in
this open access journal is 1800 CHF (Swiss Francs). Submitted papers
should be well formatted and use good English. Authors may use MDPI's
English editing service prior to publication or during author


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 End of Evolutionary Computation Digest

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