Evolutionary Computation Digest — Wednesday, 26 February 2020, Volume
34: Issue 3

SUBMISSION ADDRESS:    [log in to unmask]

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

Today's Topics:

 - 05 March: Metaheuristics Summer School—Learing & Optimization from
Big Data (Catania)

 CFPs (with submission deadline)
 - 28 February: Int. Conf. on the Practice and Theory of Automated
Timetabling (Bruges)
 - 20 March: GECCO Competition on OCP and USCP - Call for participation
 - 01 April: GECCO Competition on Multi-Task Optimization
 - 03 April: GECCO Workshops (Cancún)
 - 15 April (extended): Natural Computing special issue on
Understanding Natural Algorithm Behavior
 - 24 April: Int. Conf. on Metaheuristics and Nature Inspired
Computing (Marrakech)
 - 01 November: IEEE TEC special issue on Multi-Task Evolutionary Computation


July 8-12, 2020, Cancún, Mexico: GECCO 2020

September 7–9, 2020, Leiden, The Netherlands: PPSN 2020

Sender: Mario Pavone <[log in to unmask]>
Subject: MESS 2020 ~ Learning & Optimization from Big Data ~ Catania,
27-31 July 2020

MESS 2020 - Metaheuristics Summer School
- Learning & Optimization from Big Data -
27-31 July 2020, Catania, Italy
[log in to unmask]

** APPLICATION DEADLINE: 5th March 2020 **

MESS 2020 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 the 2020 edition is ?Learning and
Optimization from Big Data?, therefore MESS 2020 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.

All participants will have plenty of opportunities for debate and work
with leaders in the field, benefiting from direct interaction and
discussions in a stimulating environment. They will also have the
possibility to present their recently results and/or their working in
progress through oral or poster presentations, and interact with their
scientific peers, in a friendly and constructive environment.

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.


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*

Sender:  Ender Ozcan <[log in to unmask]>
Subject: Call for Papers - PATAT 2020: 13th International Conference
on the Practice and Theory of Automated Timetabling

PATAT 2020
13th International Conference on the Practice and Theory of Automated
Bruges, Belgium, August 25-28, 2020

Conference website:
Submission link:

Submission deadline: February 28, 2020

The 2020 edition of PATAT will therefore mark its silver anniversary.
Organized by KU Leuven and to be held in beautiful Bruges (Belgium)
August 25-29, 2020, PATAT 2020 promises to provide the perfect setting
for researchers and practitioners to reflect on the substantial
progress made by the timetabling academic community over the last
twenty-five years as well as to anticipate where we might head
throughout the next twenty-five. To complement this historical
reflection and anticipation of the future, a range of exciting plenary
talks will be given by experts in established areas of timetabling as
well as newly emerging ones.


Topics of interest and themes of the conference include, but not limited to:

- Educational Timetabling
- Timetabling in Transport
- Employee Rostering
- Sports Timetabling
- Timetabling in Healthcare
- Mathematical Programming
- Constraint-Based Methods
- Knowledge Based Systems
- Fuzzy Systems
- Heuristic Search
- Metaheuristics (e.g., Evolutionary Computation, Simulated Annealing,
Tabu Search, Ant Colony Methods)
- Systems to Build Systems (e.g., Hyper-heuristics, Algorithm
- Algorithm Configuration
- Artificial Intelligence
- Graph Colouring
- Resource Capacity Planning
- Parallel/Distributed Computing
- Hybrid Methods (e.g., Memetic Computing, Matheuristics)
- Machine Learning (e.g., Data Mining, Classifier Systems, Neural Networks)
- Expert Systems
- Multi-objective Approaches
- Multi-criteria Decision Making
- Foundational Studies (e.g., Complexity Issues)
- Timetabling Tools and Applications (e.g., Interactive and Batch
Systems, Standard Data Formats, Ontologies, Experiences)

Paper Submission Deadline: 28 February 2020
Notification of Acceptance: 30 April, 2020
Early Registration Closes: 15 June, 2020
Conference: 25-28 August, 2020

Sender:  Julien Lepagnot <[log in to unmask]>
Subject: GECCO 2020 Competition on OCP and USCP - Call for
participation [kind reminder]

Dear colleagues,

This is just a gentle reminder to not forget to register to the GECCO
2020 Competition on OCP and USCP.

Please note that, if you would like to submit a GECCO Companion
abstract in addition to taking part in this competition, then
registration is required no later than March 20, 2020.

If you are not interested in submitting a GECCO Companion abstract,
then registration is required no later than May 22, 2020.

Registration is mandatory in order to compete, but it is also quick
and free: simply send an email to [log in to unmask] to
declare your intention to compete (it is also worth noting that taking
part in this competition does not require a GECCO registration, unless
a submitted GECCO Companion abstract is accepted for publication).

Early registration is strongly encouraged, so that the organizing
committee is aware of all entrant teams, and can then keep them
informed of any update regarding the organization of the competition
(e.g. deadline extension).

For a short description of this competition, please refer to the call
for participation just below.



Dear colleagues,

we are pleased to invite you to take part in the 1st Competition on
the Optimal Camera Placement Problem (OCP) and the Unicost Set
Covering Problem (USCP) that will be part of the next Genetic and
Evolutionary Computation Conference (GECCO 2020, at Cancun, Mexico,
8-12 July 2020).


If an area is defined as a set of three-dimensional sample points to
be covered, and if camera configurations are sampled into so-called
candidates each with a given set of position and orientation
coordinates, then the optimal camera placement problem (OCP) comes
down to select the smallest subset of candidates which covers all the

The main goal of this competition is to encourage innovative research
works by proposing to solve challenging OCP problem instances stated
as USCP.

The contest gathers 69 OCP problem instances: 32 of them are academic
problems (various sizes and discretizations of an empty room modeled
by a rectangular cuboid with cameras on the ceiling), and 37 of them
are real-world problems (various sizes and discretizations of urban
areas with cameras on the walls of the buildings).

Details of the competition (problem instances, data formats,
competition tracks, rules for registration, submission and
evaluation,...) are available at :


In addition to their competition entries, participants will have the
opportunity to submit a short description of their algorithm for
publication in the GECCO Companion (2-page contribution).


March 20, 2020 : Early competition registration deadline (needed for
GECCO Companion submissions)
April 3, 2020 : Submission deadline for GECCO Companion abstracts
April 17, 2020 : Notification of acceptance for GECCO Companion abstracts
May 22, 2020 : Late competition registration deadline
June 5, 2020 : End of the competition, i.e. solution submission deadline
July 8-12, 2020 : GECCO conference, and announcement of the competition results

Sender:  EC-Digest Editor
Subject: GECCO Competition on Multi-Task Optimization

We invite submissions to the this year's GECCO Competition on
Multi-Task Optimization.  Participants in this competition may target
at either or both of mult-task single-objective (MTSOO)  benchmark or
the multi-task multi-objective benchmark (MTMOO) while using all
benchmark problems in the corresponding test suites.

Submissions must be sent to [log in to unmask] by April 01, 2020.

For instructions and more details on the benchmark software and its
background motivation, see the following URL:

Sender:  EC-Digest Editor
Subject: GECCO Workshops

This month the EC-Digest received CFPs from the following GECCO
Workshops.  All the workshops share the following important dates:

- Submission opening: February 27, 2020
- Paper Submission deadline: April 3, 2020
- Conference dates: July 8-12, 2020

NeuroEvolution at Work
Sender: Antonio Della Cioppa <[log in to unmask]>

Parallel and Distributed Evolutionary Inspired Methods
Sender: Antonio Della Cioppa <[log in to unmask]>

Sender: Peter Korosec <[log in to unmask]>
Subject: CfP extension: Natural Computing - Special Issue on
Understanding Natural Computing Algorithm Behaviour

Due to several requests, we have decided to extend the deadline to
April 15, 2020!
Please also note that there is a small change in instructions how to
correctly submit the manuscript!


Natural Computing (Impact Factor: 1.330)
Special issue on
Understanding Natural Computing Algorithm Behaviour




Understanding of optimization algorithm’s behavior is a vital part that
is needed for quality progress in the field of stochastic optimization
algorithms. Too often (new) algorithms are setup and tuned only
focusing on achieving the desired optimization goal. While this might
be effective and efficient in short term, in long term this is
insufficient due to the fact that this needs to be repeated for every
new problem that arises. Such approach provides only minor immediate
gains, instead of contributing to the progress in research on
optimization algorithms. To be able to overcome this deficiency, we
need to establish new standards for understanding optimization
algorithm behavior, which will provide understanding of the working
principles behind the stochastic optimization algorithms. This includes
theoretical and empirical research, which would lead to providing
insight into answering questions such as (1) why does an algorithm work
for some problems but does not work for others, (2) how to explore the
fitness landscape to gain better understanding of the algorithm’s
behavior, and (3) how to interconnect stochastic optimization and
machine learning to improve the algorithm’s behavior on new unseen

The focus of this special issue is to highlight theoretical and
empirical research that investigate approaches needed to analyze
stochastic optimization algorithms and performance assessment with
regard to different criteria. The main goal is to bring the problem and
importance of understanding optimization algorithms closer to
researchers and to show them how and why this is important for future
development in the optimization community. This will help
researchers/users to transfer the gained knowledge from theory into the
real world, or to find the algorithm that is best suited to the
characteristics of a given real-world problem.


This special issue seeks to provide an opportunity for researchers to
present their original contributions on understanding of optimization
algorithm behavior, and any related issues. The special issue topics
include (but are not limited to) the following:

- Data-driven approaches (machine learning/information
theory/statistics) for assessing algorithm performance
- Vector embeddings of problem search space
- Meta-learning
- New advances in analysis and comparison of algorithms
- Operators influence on algorithm behavior
- Parameters influence on algorithm behavior
- Theoretical algorithm analysis


The submitted manuscripts must not have been published or
simultaneously submitted elsewhere. For the submitted extended papers,
an extension of at least 30% beyond that in the published proceedings
is expected. Each submitted paper (extended or not) will receive
thorough reviews and evaluation. Papers will be selected based mainly
on their originality, scientific and technical quality of the
contributions, organization and presentation and relevance to the
special issue. The NACO’s submission system is already open for
submissions. When submitting your manuscript please select "Original
article" as article type. Then, later under "Additional Information”,
there is a question "Does this manuscript belong to a special issue?".
There you have to select "S.I.: Understanding Evolutionary Algorithm
Behaviour". Please submit your manuscript before April 15, 2020.

Once your manuscript is accepted, it will go into production, and will
be published in 2021.

Please ensure you read the Guide for Authors before writing your
manuscript. The Guide for Authors and link to submit your manuscript is
available on the Journal's homepage at:

Inquiries, including questions about appropriate topics, may be sent
electronically to the Guest Editors.

IMPORTANT DATES (Subject to change)

- Paper submission due: April 15, 2020
- First-round acceptance decision notification: June 30, 2020
- First revision submission due: August 31, 2020
- Second-round acceptance decision notification: November 30, 2020
- Second revision submission due: December 31, 2020
- Notification of final decision: February 28, 2021
- Target (tentative) publication date: 2021

Sender:  "Grégoire DANOY" <[log in to unmask]>
Subject: CFP META'2020 @Marrakech

International Conference on Metaheuristics and Nature Inspired Computing

                         27-31 Oct 2020
                       Marrakech, Morocco


META is one of the main event focusing on the progress of the area of
metaheuristics and their applications. As in previous editions,
META’2020 will provide an opportunity to the international research
community in metaheuristics to discuss recent research results, to
develop new ideas and collaborations, and to meet old friends and make
new ones in a friendly and relaxed atmosphere.

META'2020 welcomes presentations that cover any aspects of metaheuristic
research such as new algorithmic developments, high-impact applications,
new research challenges, theoretical developments, implementation
issues, and in-depth experimental studies. META'2020 strives for a
high-quality program that will be completed by a number of invited
talks, tutorials, workshops and special sessions.

Important dates

- Submission deadline: April 24, 2020
- Notification of acceptance: May 30, 2020

Sender:  EC-Digest editor
Subject: IEEE TEC special issue on Multi-Task Evolutionary Computation

IEEE Transactions on Evolutionary Computation
Special Issue on Multi-task Evolutionary Computation

Despite the vast amounts of data (i.e., evaluated solution samples)
generated in each run of an EC algorithm, a common feature of existing
implementations is that they do not learn with experience. Every
problem is essentially solved from scratch, ignoring recurring
solution patterns that may exist in the data of a related task. This
is much in contrast to human experts, who, by virtue of their acquired
knowledge, are able to arrive at quick decisions by simply leveraging
on what they already know. It may thus be argued that the practical
utility of EC is yet to be fully tapped, as the general lack of
inter-task knowledge transfer ability can render them ineffective for
highly complex / deceptive tasks or those requiring optimizations
within short time scales.

Given the above, the key aim of this special issue (SI) is to advance
theories and methodologies in the emerging subject of multi-task EC
(also referred to as evolutionary multitasking). The focus shall be on
novel algorithms that exploit the population-based search strategy of
EC to tackle multiple optimization problems in unison. Most
importantly, proposed algorithms must depict some form of direct or
indirect knowledge exchange between tasks; for instance, through
crossover-based implicit genetic transfers (as in multifactorial
evolutionary algorithms), cross-task solution sampling, etc. On the
whole, the salient feature of the SI lies in its learning-centric view
of EC, enabling associated algorithms to automatically extract, adapt,
integrate and reuse data from related tasks to orchestrate efficient
search behaviors on the fly.

Find the full CFP for the special issue at the following URL:


Submission open: May 1, 2020
Submission deadline: November 1, 2020
Tentative publication date: 2021


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 End of Evolutionary Computation Digest