Wednesday, April 3, 2019

[DMANET] (BB-DOB@GECCO 2019) Extended Deadline 10 April 2019: Workshop on Black-Box Discrete Optimization Benchmarking (Call For Contributions)

Extended deadline: April 10, 2019

Call for Papers: Black Box Discrete Optimization Benchmarking (BB-DOB)
Workshop
The Genetic and Evolutionary Computation Conference (GECCO 2019)
July 13-17, 2019, Prague, Czech Republic
http://iao.hfuu.edu.cn/bbdob-gecco19

The Black-Box Discrete Optimization Benchmarking (BB-DOB) Workshop, a part
of the Genetic and Evolutionary Computation Conference (GECCO) 2019, is
cordially inviting the submission of original and unpublished research
papers.

The Black-Box-Optimization Benchmarking (BBOB) methodology associated to
the BBOB-GECCO workshops has become a well-established standard for
benchmarking stochastic and deterministic continuous optimization
algorithms. The aim of the BB-DOB workshop series is to set up a process
that will allow to achieve a similar standard methodology for the
benchmarking of black box optimization algorithms in discrete and
combinatorial search spaces.

The long term aim of our workshop series is to produce, for the domain of
discrete optimization:

(1) a well-motivated benchmark function testbed,
(2) an experimental set-up,
(3) generation of data output for post-processing and
(4) presentation of the results in graphs and tables.

The aims of this GECCO 2019 BB-DOB workshop are to finalize the
benchmarking testbed for discrete optimization and to promote a discussion
of which performance measures should be used.

The benchmark functions should capture the difficulties of combinatorial
optimization problems in practice. They also should be comprehensible so
that algorithm behaviors can be understood or interpreted according to the
performance on a given benchmark problem. The goal is that a desired search
behavior can be pictured and algorithm deficiencies can be understood in
depth. This understanding will lead to the design of improved algorithms.
Ideally, we would like the benchmark functions to be scalable with the
problem size and non-trivial in the black box optimization sense (the
function may be shifted such that the global optimum may be any point).
Achieving this goal would help greatly in bridging the gap between
theoreticians and experimentalists.

We also wish to investigate which measures should be used to compare
algorithm performance, which statistical tests should be run to compare
algorithms, and how to deal with unsuccessful runs.

This workshop wants to bring together experts on benchmarking of
optimization algorithms. It will provide a common forum for discussions and
exchange of opinions. Interested participants are encouraged to submit a
paper related to black-box optimization benchmarking of discrete
optimizers. The topics of interesting especially include papers that

- suggest functions to be included in the benchmark and motivate the
reasons for inclusion,
- suggest benchmark function properties that allow to capture
difficulties which occur in real-world applications (e.g., deception,
separability, etc.),
- suggest which classes of standard combinatorial optimization problems
should be included and how to select significant instances,
- suggest which classes of toy problems should be included and motivate
why,
- suggest which performance measures should be used to analyze and
compare algorithms and comment/suggestions on related issues, and/or
- tackle any other aspect of benchmarking methodology for discrete
optimizers such as design of experiments, presentation methods,
benchmarking frameworks, etc.
- conduct performance comparisons, landscape analysis, discussion of
selected benchmark problems and/or provided statistics of IOHprofiler (
https://github.com/IOHprofiler), a ready-to-use software for the empirical
analysis of iterative optimization heuristics

For more information please contact Pietro S. Oliveto at
p.oliveto@sheffield.ac.uk.
This workshop is organized as part of ImAppNIO Cost Action 15140.


1. Important Dates

Paper Submission Opening: 27 February 2019
Paper Submission Deadline (FINAL): 10 April 2019
Decisions Due: 17 April 2019
Camera-Ready Material due: 24 April 2019
Author Registration Deadline: 24 April 2019
Conference Presentation: 13-14 July 2019


2. Instructions for Authors

Instructions regarding how to submit papers and the paper format are given
at https://gecco-2019.sigevo.org/index.html/tiki-index.php?page=Workshops.

Some of the things to consider are:

- Submitted papers must be ANONYMIZED, i.e., cannot contain any element
that may reveal the identity of their authors, in order to facilitate a
double-blind review process.
- The maximum paper length is eight pages.
- The maximum number of words in the abstract is 200.
- In the GECCO submission page, select "Workshop Paper" and in the field
"Workshop" of the next form, select "Workshop Black Box Discrete
Optimization Benchmarking".
- At least one author from each accepted paper must register at the
conference by April 24, 2019, pay the conference fee, and be present at the
conference to give an oral presentation.


3. Chairs

- Carola Doerr, Sorbonne University, Paris, France
- Pietro S. Oliveto, University of Sheffield, UK
- Thomas Weise, Institute of Applied Optimization, Hefei University, Hefei,
China
- Borys Wróbel, Adam Mickiewicz University, Poland
- Aleš Zamuda, University of Maribor, Slovenia


4. International Program Committee

- Abhishek Awasthi, University of Applied Sciences Zittau/Görlitz, Görlitz,
Germany
- Thomas Bartz-Beielstein, Technical University of Cologne, Köln (Cologne),
Germany
- Josu Ceberio Uribe, University of the Basque Country, Bilbao, Spain
- Francisco Chicano, University of Málaga, Málaga, Spain
- Carola Doerr, Sorbonne University, Paris, France
- Johann Dréo, THALES Research & Technology, Massy, Île-de-France, France
- Aniko Ekart, Aston University, Birmingham, UK
- Thomas Jansen, Aberystwyth University, UK
- Pascal Kerschke, Westfälische Wilhelms-Universität Münster, Münster,
Germany
- Algirdas Lančinkas, Vilnius University, Lithuania
- Johannes Lengler, ETH Zürich, Zürich, Switzerland
- Bin Li, University of Science and Technology of China, Hefei, China
- Jinlong Li, University of Science and Technology of China, Hefei, China
- Xinlu Li, Institute of Applied Optimization, Hefei University, Hefei,
China
- Arnaud Liefooghe, Université de Lille Sciences et Technologies, Lille,
France
- Frank Neumann, University of Adelaide, Adelaide, SA, Australia
- Miguel Nicolau, University College Dublin, Ireland
- Pietro S. Oliveto, University of Sheffield, UK
- Chao Qian, University of Science and Technology of China, Hefei, China
- Mohammad Ali Raayatpanah, Kharazmi University, Tehran, Iran
- Roman Senkerik, Tomas Bata University, Zlin, Czech Republic
- Dirk Sudholt, University of Sheffield, UK
- Markus Ullrich, University of Applied Sciences Zittau/Görlitz, Görlitz,
Germany
- Markus Wagner, University of Adelaide, Adelaide, SA, Australia
- Hao Wang, Leiden University, Leiden, The Netherlands
- Thomas Weise, Institute of Applied Optimization, Hefei University, Hefei,
China
- Carsten Witt, Technical University of Denmark, Denmark
- Borys Wróbel, Adam Mickiewicz University, Poland
- Yuezhong Wu, University of New South Wales (UNSW), Sydney, Australia
- Zhize Wu, Institute of Applied Optimization, Hefei University, Hefei,
China
- Aleš Zamuda, University of Maribor, Slovenia
- Xingyi Zhang, Anhui University, Hefei, China


5. Chair Biographies

Carola Doerr is a permanent CNRS researcher at Sorbonne University in
Paris, France. She studied Mathematics at Kiel University (Germany, Diplom,
2007) and Computer Science at the Max Planck Institute for Informatics and
Saarland University (Germany, PhD, 2011). Before joining the CNRS she was a
post-doc at Paris Diderot University (Paris 7) and the Max Planck Institute
for Informatics. From 2007 to 2009, she worked as a business consultant for
McKinsey & Company, where her interest in evolutionary algorithms (EAs)
originates from. Her main research activities are in the mathematical
analysis of randomized algorithms, with a strong focus on EAs and other
black-box optimizers. She has been very active in the design and analysis
of black-box complexity models, a theory-guided approach to explore the
limitations of heuristic search algorithms. Most recently, she has used
knowledge from these studies to prove superiority of dynamic parameter
choices in evolutionary computation, a topic that she believes to carry
huge unexplored potential for the community. Carola Doerr has received
several awards for her work on evolutionary computation, among them the
Otto Hahn Medal of the Max Planck Society and four best paper awards at
GECCO. She is chairing the program committee of FOGA 2019 and previously
chaired the theory tracks of GECCO 2015 and 2017. She is editor of two
special issues in Algorithmica and vice chair of the EU-funded COST action
15140 on "Improving Applicability of Nature-Inspired Optimisation by
Joining Theory and Practice (ImAppNIO)".

Pietro S. Oliveto is a Senior Lecturer and an EPSRC Early Career Fellow at
the University of Sheffield,UK. He re-ceived the Laurea degree in computer
science from the University of Catania, Italy in 2005 and the PhD degree
from the University of Birmingham,UK in 2009. He has been EPSRC PhD+ Fellow
(2009-2010) and EPSRC Postdoctoral Fellow (2010-2013) at Birmingham and
Vice-Chancellor's Fellow at Sheffield (2013-2016). His main research
interest is the performance analysis of bio-inspired computation techniques
including evolutionary algorithms, genetic programming, artificial immune
systems and hyperheuristics. He has won best paper awards at GECCO 2008,
ICARIS 2011 and GECCO 2014. He is part of the Steering Committee of the
annual workshop on Theory of Randomized Search Heuristics (ThRaSH),
Associate Editor of the IEEE Transactions on Evolution-ary Computation,
Chair of the IEEE CIS Technical Committee on Evolutionary Computation,
Leader of the ImAppNIO Cost Action Working Group on Benchmarking and member
of the EPSRC Peer Review College. Dr. Oliveto has given tutorials on the
runtime complexity analysis of EAs regularly at CEC, GECCO, WCCI, SSCI and
PPSN since 2012.

Thomas Weise obtained the MSc in Computer Science in 2005 from the Chemnitz
University of Technology and his PhD from the University of Kassel in 2009.
He then joined the University of Science and Technology of China (USTC) as
PostDoc and subsequently became Associate Professor at the USTC-Birmingham
Joint Research Institute in Intelligent Computation and Its Applications
(UBRI) at USTC. In 2016, he joined Hefei University as Full Professor to
found the Institute of Applied Optimization at the Faculty of Computer
Science and Technology. Prof. Weise has more than seven years of experience
as a full time researcher in China, having contributed significantly both
to fundamental as well as applied research. He has more than 80 scientific
publications in international peer reviewed journals and conferences. His
book "Global Optimization Algorithms – Theory and Application" has been
cited more than 730 times. He has acted as reviewer, editor, or program
committee member at 70 different venues.

Borys Wróbel works at the intersection between biology and computer
science, and his current research interests include computational
properties of biologically-inspired models of computation (artificial gene
regulatory networks and spiking neural networks), which involves building
artificial life software platforms that use high-performance computing and
neuromorphic hardware. Borys Wróbel received his PhD at the University of
Gdańsk (Poland) in 1998, was a Fulbright Visiting Researcher in the Salk
Institute for Biological Studies in San Diego, CA, and later FEBS and EMBO
Fellow at the Hebrew University of Jerusalem (Israel), Marie Curie
Postdoctoral Fellow at the University of Valencia, and Sciex Fellow in the
Insitute of Neuroinformatics at the University of Zurich and ETHZ
(Switzerland). He is now a professor at the Adam Mickiewicz University in
Poznań, Poland. He is one of the vice-chairs of the ImAppNIO working group
on Benchmarking.

Aleš Zamuda is an Assistant Professor and Researcher at University of
Maribor (UM), Slovenia. He received Ph.D. (2012), M.Sc. (2008), and B.Sc.
(2006) degrees in computer science from UM. He is management committee
member for Slovenia at European Cooperation in Science (COST), actions
CA15140 (ImAppNIO - Improving Applicability of Nature-Inspired Optimisation
by Joining Theory and Practice) and IC1406 (cHiPSet - High-Performance
Modelling and Simulation for Big Data Applications). He is IEEE Senior
Member, IEEE Slovenia Section Vice Chairman and Young Professionals
Chairman, IEEE CIS member, ACM SIGEVO member, ImAppNIO Benchmarks working
group vice-chair, and associate editor for Swarm and Evolutionary
Computation (IF3.818). His areas of computer science applications include
ecosystems, evolutionary algorithms, multicriterion optimization,
artificial life, and computer animation; currently yielding h-index 18, 41
publications, and 883 citations on Scopus. He won IEEE R8 SPC 2007 award,
IEEE CEC 2009 ECiDUE, 2016 Danubuius Young Scientist Award, and 1% top
reviewer at 2017 and 2018 Publons Peer Review Awards, including reviews for
over 40 journals and 85 conferences.


6. Hosting Event

The Genetic and Evolutionary Computation Conference (GECCO 2019)
July 13-17, 2019, Prague, Czech Republic
http://gecco-2019.sigevo.org

The Genetic and Evolutionary Computation Conference (GECCO 2019) will
present the latest high-quality results in genetic and evolutionary
computation. Topics include genetic algorithms, genetic programming,
evolution strategies, evolutionary programming, memetic algorithms,
hyper-heuristics, real-world applications, evolutionary machine learning,
evolvable hardware, artificial life, adaptive behavior, ant colony
optimization, swarm intelligence, biological applications, evolutionary
robotics, coevolution, artificial immune systems, and more. The full list
of tracks is available at:
https://gecco-2019.sigevo.org/index.html/Program+Tracks

The GECCO 2019 Program Committee invites the submission of technical papers
describing your best work in genetic and evolutionary computation. Full
papers of at most 8 pages (excluding references) should present original
work that meets the high-quality standards of GECCO. Accepted full papers
appear in the ACM digital library as part of the Main Proceedings of GECCO.
For full papers, a separate abstract needs to be submitted first by January
30, 2019. Full papers are due by the non-extensible deadline of February 6,
2019.

Each paper submitted to GECCO will be rigorously evaluated in a
double-blind review process. Evaluation is done on a per-track basis,
ensuring high interest and high expertise of the reviewers. Review criteria
include the significance of the work, technical soundness, novelty,
clarity, writing quality, relevance and, if applicable, sufficiency of
information to permit replication.

Besides full papers, poster-only papers of at most 2 pages may be
submitted. Poster-only papers should present original work that has not yet
reached the maturity and completeness of research results that are
published as full papers at GECCO. The review of poster-only papers follows
the same double-blind process described above. Accepted poster-only papers
will appear in the ACM digital library as part of the Companion Proceedings
of GECCO. Poster-only papers are due by the non-extensible deadline of
February 6, 2019, and no abstract needs to be submitted first.

By submitting a paper, the author(s) agree that, if their paper is
accepted, they will:

- Submit a final, revised, camera-ready version to the publisher on or
before the camera-ready deadline
- Register at least one author to attend the conference on April 17, 2019
- Attend the conference (at least one author)
- Present the accepted paper at the conference

Each paper accepted needs to have at least one author registered. If an
author is presenting more than one paper at the conference, she/he does not
pay any additional registration fees.


7. Related Events

Special Issue on Benchmarking of Computational Intelligence Algorithms,
Applied Soft Computing, Elsevier B.V., http://iao.hfuu.edu.cn/bocia-asoc-si
Special Session on Benchmarking of Evolutionary Algorithms for Discrete
Optimization (BEADO), 2019 IEEE Congress on Evolutionary Computation
(CEC'19), June 10-13, 2019 in Wellington, New Zealand ,
http://iao.hfuu.edu.cn/beado19

--
Pietro S. Oliveto
Senior Lecturer,
EPSRC Early Career Fellow,
Department of Computer Science,
The University of Sheffield, Sheffield, UK.
*www.dcs.shef.ac.uk/people/P.Oliveto/rig/
<http://www.dcs.shef.ac.uk/people/P.Oliveto/rig/>*

*Fully funded PhD studentships available now* in time complexity analysis
of bio-inspired computation. Enquiries by excellent candidates can be sent
to me by email. Applications will be accepted until the posts are filled.
Further details are here
<http://staffwww.dcs.shef.ac.uk/people/P.Oliveto/PhDStudentships.html>.
Applicants should apply using the online application form here
<http://www.shef.ac.uk/postgraduate/online>

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