[hpc-announce] 1st GECCO Workshop on Decomposition Techniques in Evolutionary Optimization (DTEO)

bilel derbel bilel.derbel at univ-lille1.fr
Fri Feb 9 08:50:42 CST 2018

1st GECCO Workshop on Decomposition Techniques in Evolutionary 
Optimization (DTEO)

To be Held in conjunction with the 27th ACM Genetic and Evolutionary 
Computation Conference (GECCO 2018)

Kyoto, Japan, 15-19 July 2018

Submission deadline:     27 March 2018
Acceptance notification: 10 April 2018
Camera-ready deadline:   24 April 2018
Workshop date:           15 or 16 July 2018

Tackling an optimization problem using decomposition consists in 
transforming (or re-modeling or re-thinking) it into multiple, a priori 
smaller and easier, problems that can be solved cooperatively. A number 
of techniques are being actively developed by the evolutionary computing 
community in order to explicitly or implicitly design decomposition with 
respect to four facets of an optimization problem: (i) the environmental 
parameters, (ii) the decision variables, (iii) the objective functions, 
and (iv) the available computing resources. The workshop aims to be a 
unified opportunity to report the recent advances in the design, 
analysis and understanding of evolutionary decomposition techniques and 
to discuss the current and future challenges in applying decomposition 
to the increasingly big and complex nature of optimization problems 
(e.g., large number of variables, large number of objectives, 
multi-modal problems, simulation optimization, uncertain scenario-based 
optimization) and its suitability to modern large scale compute 
environments (e.g., massively parallel and decentralized algorithms, 
large scale divide-and-conquer parallel algorithms, expensive 

The workshop focus is there-by on (but not limited to) the 
developmental, implementational, theoretical and applied aspects of:

* Large scale evolutionary decomposition, e.g., decomposition in 
decision space, co-evolutionary algorithms, grouping and cooperative 
techniques, decomposition for constraint handling

* Multi- and Many- objective decomposition, e.g., aggregation and 
scalarizing approaches, cooperative and hybrid island-based design, 
(sub-)population decomposition and mapping

* Parallel and distributed evolutionary decomposition, e.g., scalability 
with respect to decision and objective spaces, divide-and-conquer 
decentralized techniques, distribution of compute efforts, scalable 
deployments on heterogeneous and massively parallel compute environments

* Novel general purpose decomposition techniques, e.g., machine-learning 
and model assisted decomposition, offline and on-line configuration of 
decomposition, search region decomposition and multiple surrogates, 
parallel expensive optimization

* Understanding and benchmarking decomposition techniques

* General purpose software tools and libraries for evolutionary 

We invite submissions of the following types of papers:
  - research papers (up to 8 pages)
  - position papers (up to 2 pages)

Accepted papers will be presented during the workshop and will appear in 
the GECCO Companion ACM proceedings. Paper's format should follow the 
GECCO 2018 ACM instructions.

Submissions of early and in-progress work are encouraged. Authors of 
accepted papers proposing novel software developments will be encouraged 
to give a demo or a short introductory tutorial. Authors of accepted 
papers describing novel software or technical developments will be 
encouraged to give a demonstration during the workshop.

- Bilel Derbel, University of Lille, Inria, France (contact : bilel dot 
derbel at univ-lille1 dor fr )
- Ke Li, University of Exeter, UK
- Xiaodong Li, RMIT University, Melbourne, Australia
- Saúl Zapotecas, UAM-Cuajimalpa, México
- Qingfu Zhang, City University, Hong Kong
- Hui Li, Xian Jiaotong University, China

More Information

Associate Professor
Univ. Lille — CRIStAL (CNRS UMR 9189)
BONUS team — Inria Lille - Nord Europe
International Associated Laboratory LIA-MODO, France/Japan

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