posted by organizer: almarahat || 17991 views || tracked by 3 users: [display]

SAEOpt 2021 : Workshop on Surrogate-Assisted Evolutionary Optimisation


When Jul 10, 2021 - Jul 14, 2021
Where Online - Lille
Submission Deadline Apr 12, 2021
Notification Due Apr 26, 2021
Final Version Due May 3, 2021
Categories    evolutionary computation   optimization   surrogate-assisted   machine learning

Call For Papers

In many real-world optimisation problems evaluating the objective function(s) is expensive, perhaps requiring days of computation for a single evaluation. 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, including continuous and discrete variable problems, although little work has been done on combinatorial problems. Surrogates have been employed in solving a variety of optimisation problems, such as multi-objective optimisation, dynamic optimisation, and robust optimisation. Surrogate-assisted methods have also found successful applications to aerodynamic design optimisation, structural design optimisation, data-driven optimisation, chip design, drug design, robotics and many more. Most interestingly, the need for on-line learning of the surrogates has led to a fruitful crossover between the machine learning and evolutionary optimisation communities, where advanced learning techniques such as ensemble learning, active learning, semi-supervised learning and transfer learning have been employed in surrogate construction.

Despite recent successes in using surrogate-assisted evolutionary optimisation, there remain many challenges. This workshop aims to promote the research on surrogate assisted evolutionary optimisation including the synergies between evolutionary optimisation and learning. Thus, this workshop will be of interest to a wide range of GECCO participants. Particular topics of interest include (but are not limited to):

* Bayesian optimisation
* Advanced machine learning techniques for constructing surrogates
* Model management in surrogate-assisted optimisation
* Multi-level, multi-fidelity surrogates
* Complexity and efficiency of surrogate-assisted methods
* Small and big data-driven evolutionary optimisation
* Model approximation in dynamic, robust and multi-modal optimisation
* Model approximation in multi- and many-objective optimisation
* Surrogate-assisted evolutionary optimisation of high-dimensional problems
* 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
* Test problems for surrogate-assisted evolutionary optimisation
* Performance improvement techniques in surrogate-assisted evolutionary computation
* Performance assessment of surrogate-assisted evolutionary algorithms

We invite short papers of up to 8 pages (excluding references) 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 (including references) 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

Keynote speaker: Prof. Thomas Bartz-Beielstein of Technical University of Cologne, one of the most distinguished researchers in the field, will give a keynote speech at the workshop on the topic. For more information, visit:

** Important Dates **

Submission site opens: 11 February, 2021.
Submission deadline: 12 April, 2021.
Notification of acceptance: 26 April, 2021.
Camera-ready submission: 03 May, 2021.
Author registration deadline: 03 May, 2021.
Conference date: 10 - 14 July, 2021.

** Submission **

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

Manuscripts should not exceed eight pages (excluding references) for regular submissions and two pages for position papers (including references). For proposals of short demonstrations or presentations (5-10 minutes), a half-page abstract should be submitted. This year all submissions will be handled through the standard GECCO submission site:

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

For more information, visit:

Best regards,
Alma Rahat.

On behalf of the organisers of SAEOpt:
Dr Alma Rahat, Swansea
Prof. Richard Everson, Exeter
Prof. Jonathan Fieldsend, Exeter
Prof. Handing Wang, Xidian
Prof. Yaochu Jin, Surrey

Related Resources

AABOH 2023   Analysing algorithmic behaviour of optimisation heuristics - Workshop
ICDM 2023   International Conference on Data Mining
EvoCOP 2023   Evolutionary Computation in Combinatorial Optimization
JCRAI 2023-Ei Compendex & Scopus 2023   2023 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2023)
IEEE CEC 2023   IEEE Congress on Evolutionary Computation
JCICE 2024   2024 International Joint Conference on Information and Communication Engineering(JCICE 2024)
GECCO 2023   Genetic and Evolutionary Computation Conference
IEEE Xplore-Ei/Scopus-CCCAI 2023   2023 International Conference on Communications, Computing and Artificial Intelligence (CCCAI 2023) -EI Compendex
IEEE SSCI 2023   2023 IEEE Symposium Series on Computational Intelligence
MLDM 2024   20th International Conference on Machine Learning and Data Mining