Tuesday, March 12, 2019

[DMANET] 2nd GECCO Workshop on Decomposition Techniques in Evolutionary Optimization (DTEO)

2nd GECCO Workshop on Decomposition Techniques in Evolutionary
Optimization (DTEO)

To be Held in conjunction with the 28th ACM Genetic and Evolutionary
Computation Conference (GECCO 2019)

Prague, Czech Republic, 13-17 July 2019

Submission deadline:     03 April 2019
Acceptance notification: 17 April 2019
Camera-ready deadline:   24 April 2019
Workshop date:           13 or 17 July 2019

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 optimization and
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
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 optimization).

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

* Large scale 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 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

* General purpose decomposition-related 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 2019 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
- Ke Li, University of Exeter, UK
- Xiaodong Li, RMIT University, Melbourne, Australia
- Saúl Zapotecas, UAM-Cuajimalpa, México
- Qingfu Zhang, City University, Hong Kong

More Information

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