[robotics-worldwide] [news] CFP: Workshop on Surrogate-Assisted Evolutionary Optimisation (SAEOpt, GECCO, 2017)

Alma Rahat almarahat at gmail.com
Wed Dec 7 02:47:50 PST 2016


Workshop on  Surrogate-Assisted Evolutionary Optimisation (SAEOpt 2017)

** Call for Papers **
--------------------------

In many real world optimisation problems evaluating the objective 
function(s) is computationally expensive. Surrogate-assisted 
optimisation attempts to alleviate this problem by employing 
computationally cheap 'surrogate' models to estimate the objective 
function(s) or the ranking relationships of the candidate solutions. 
Surrogate-assisted approaches have been widely used across the field of 
evolutionary optimisation, and successful applications include 
aerodynamic design optimisation, structural design optimisation, 
data-driven optimisation, chip design, drug design, robotics and many more.

Despite recent successes in using surrogate-assisted evolutionary 
optimisation, there remain many challenges. The Workshop on 
Surrogate-Assisted Evolutionary Optimisation (SAEOpt) to be held at 
GECCO 2017 in Berlin, Germany, aims to promote the research on 
surrogate-assisted evolutionary optimisation, particularly the synergies 
between evolutionary optimisation and machine learning. Topics of 
interest include (but are not limited to):

* Advanced machine learning approaches for constructing surrogates
* Model management in surrogate-assisted optimisation
* Multi-level, multi-fidelity surrogates
* Complexity and efficiency of surrogate-assisted methods
* Surrogates-assisted evolutionary optimisation of computationally 
expensive problems
* Data-driven optimisation
* Model approximation in dynamic, robust and multi-modal optimisation
* Model approximation in multi- and many-objective optimisation
* Comparison of different modelling methods in surrogate construction
* Surrogate-assisted identification of the feasible region
* Comparison of evolutionary and non-evolutionary approaches with 
surrogate models
* Performance assessment and improvement techniques in 
surrogate-assisted evolutionary computation

We invite short papers of up to 8 pages presenting novel developments in 
one or more of these areas, or other areas relevant to 
surrogate-assisted evolutionary optimisation. We welcome position papers 
of up to 2 pages showcasing exciting exploratory and preliminary results.

We also welcome proposals for short demonstrations or presentations 
(5-10 minutes) on the following topics:

* Surrogate-assisted optimisation in real world
* Contemporary test problems in surrogate-assisted optimisation
* Other relevant accepted GECCO papers or recent journal papers

** Important Dates **
-----------------------------

Submission deadline: 27 March, 2017.
Notification of acceptance: 10 April, 2017.
Camera ready submission: TBA.
Conference date: 15 - 19 July, 2017.

** Submission **
----------------------

Accepted papers will be presented orally (20 minutes) at the workshop 
and distributed in the workshop proceedings to all conference attendees. 
Authors should follow the format of the GECCO manuscript style; further 
details are available in the following link.

https://urldefense.proofpoint.com/v2/url?u=http-3A__gecco-2D2017.sigevo.org_index.html_Papers-2Bsubmission-2Binstruction&d=DgICaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=W8VPlLvIHJIccvtuO-i8FqIYMBsPMCM86TH-9LPjzsc&s=iQzLpqS-w51F_uMyQ1uC9SKHC0wfgnoTAxbb_aeVmaE&e= 

Manuscripts should not exceed eight pages for regular submission and two 
pages for position papers. For proposals of short demonstrations or 
presentations (5-10 minutes), a half page abstract should be submitted. 
All submissions should be sent in PDF format to: saeopt at exeter.ac.uk.

Please note that acceptance to workshop will be based on double-blind 
peer review of the submitted papers.

For more information, visit: https://urldefense.proofpoint.com/v2/url?u=http-3A__www.saeopt.ex.ac.uk_&d=DgICaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=W8VPlLvIHJIccvtuO-i8FqIYMBsPMCM86TH-9LPjzsc&s=rzHlgcRrFPBBqwB3ePAXNYTIFLuB3g5TTJYqyb-reW0&e= 


-- 
*Dr Alma A. M. Rahat*
Research Fellow,
Department of Computer Science,
College of Engineering, Mathematics and Physical Sciences,
University of Exeter,
United Kingdom.
Tel: +44 (0) 1392 723913
https://urldefense.proofpoint.com/v2/url?u=https-3A__emps.exeter.ac.uk_computer-2Dscience_staff_aamr201&d=DgICaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=W8VPlLvIHJIccvtuO-i8FqIYMBsPMCM86TH-9LPjzsc&s=Bje0m2Fhbec1HVHf2k3rsEiSRcDw0EXY4eQGo3q5a_U&e= 


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